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| last_modified
timestamp[us, tz=UTC]date 2020-02-15 11:33:14
2025-07-15 06:27:42
| downloads
int64 0
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| likes
int64 0
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| library_name
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Chris1/ppo-CarRacing-v0 | Chris1 | 2022-07-25T20:26:10Z | 7 | 0 | stable-baselines3 | [
"stable-baselines3",
"CarRacing-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
]
| reinforcement-learning | 2022-07-25T20:25:35Z | ---
library_name: stable-baselines3
tags:
- CarRacing-v0
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- metrics:
- type: mean_reward
value: 205.45 +/- 120.65
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CarRacing-v0
type: CarRacing-v0
---
# **PPO** Agent playing **CarRacing-v0**
This is a trained model of a **PPO** agent playing **CarRacing-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL Zoo)
RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
SB3: https://github.com/DLR-RM/stable-baselines3<br/>
SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
```
# Download model and save it into the logs/ folder
python -m utils.load_from_hub --algo ppo --env CarRacing-v0 -orga Chris1 -f logs/
python enjoy.py --algo ppo --env CarRacing-v0 -f logs/
```
## Training (with the RL Zoo)
```
python train.py --algo ppo --env CarRacing-v0 -f logs/
# Upload the model and generate video (when possible)
python -m utils.push_to_hub --algo ppo --env CarRacing-v0 -f logs/ -orga Chris1
```
## Hyperparameters
```python
OrderedDict([('batch_size', 128),
('clip_range', 0.2),
('ent_coef', 0.0),
('env_wrapper',
[{'utils.wrappers.FrameSkip': {'skip': 2}},
{'gym.wrappers.resize_observation.ResizeObservation': {'shape': 64}},
{'gym.wrappers.gray_scale_observation.GrayScaleObservation': {'keep_dim': True}}]),
('frame_stack', 2),
('gae_lambda', 0.95),
('gamma', 0.99),
('learning_rate', 'lin_1e-4'),
('max_grad_norm', 0.5),
('n_envs', 8),
('n_epochs', 10),
('n_steps', 512),
('n_timesteps', 4000000.0),
('normalize', "{'norm_obs': False, 'norm_reward': True}"),
('policy', 'CnnPolicy'),
('policy_kwargs',
'dict(log_std_init=-2, ortho_init=False, activation_fn=nn.GELU, '
'net_arch=[dict(pi=[256], vf=[256])], )'),
('sde_sample_freq', 4),
('use_sde', True),
('vf_coef', 0.5),
('normalize_kwargs', {'norm_obs': False, 'norm_reward': False})])
```
|
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-5_belgium-5_s452 | jonatasgrosman | 2022-07-25T20:25:57Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T20:25:45Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_xls-r_accent_france-5_belgium-5_s452
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-8_female-2_s287 | jonatasgrosman | 2022-07-25T20:01:41Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T20:01:29Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_gender_male-8_female-2_s287
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-8_female-2_s235 | jonatasgrosman | 2022-07-25T19:56:44Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T19:56:33Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_gender_male-8_female-2_s235
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
WAS/portrait-diffusion | WAS | 2022-07-25T19:55:28Z | 0 | 1 | null | [
"license:cc-by-nc-4.0",
"region:us"
]
| null | 2022-07-25T07:16:06Z | ---
license: cc-by-nc-4.0
---
#@markdown ####**Custom Model Settings:**
if diffusion_model == 'custom':
model_config.update({
'attention_resolutions': '32, 16, 8',
'class_cond': False,
'diffusion_steps': 1000,
'rescale_timesteps': True,
'image_size': 512,
'learn_sigma': True,
'noise_schedule': 'linear',
'num_channels': 128,
'num_heads': 4,
'num_res_blocks': 2,
'resblock_updown': True,
'use_checkpoint': use_checkpoint,
'use_fp16': True,
'use_scale_shift_norm': True,
}) |
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-2_female-8_s786 | jonatasgrosman | 2022-07-25T19:51:49Z | 4 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T19:51:37Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_gender_male-2_female-8_s786
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-2_female-8_s772 | jonatasgrosman | 2022-07-25T19:46:15Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T19:46:05Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_gender_male-2_female-8_s772
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-2_female-8_s182 | jonatasgrosman | 2022-07-25T19:41:41Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T19:41:27Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_gender_male-2_female-8_s182
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-10_female-0_s840 | jonatasgrosman | 2022-07-25T19:36:56Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T19:36:45Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_gender_male-10_female-0_s840
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
heriosousa/Reinforce-Pixelcopter-PLE-v0 | heriosousa | 2022-07-25T19:28:22Z | 0 | 0 | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
]
| reinforcement-learning | 2022-07-25T19:28:15Z | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-Pixelcopter-PLE-v0
results:
- metrics:
- type: mean_reward
value: 16.50 +/- 12.64
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
---
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: https://github.com/huggingface/deep-rl-class/tree/main/unit5
|
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-0_female-10_s961 | jonatasgrosman | 2022-07-25T19:22:34Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T19:22:20Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_gender_male-0_female-10_s961
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-5_female-5_s294 | jonatasgrosman | 2022-07-25T19:02:57Z | 4 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T19:02:43Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_gender_male-5_female-5_s294
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-8_nortepeninsular-2_s507 | jonatasgrosman | 2022-07-25T18:48:16Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T18:48:05Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_accent_surpeninsular-8_nortepeninsular-2_s507
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-8_nortepeninsular-2_s187 | jonatasgrosman | 2022-07-25T18:43:16Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T18:43:04Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_accent_surpeninsular-8_nortepeninsular-2_s187
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-10_nortepeninsular-0_s885 | jonatasgrosman | 2022-07-25T18:22:30Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T18:22:17Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_accent_surpeninsular-10_nortepeninsular-0_s885
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-0_nortepeninsular-10_s157 | jonatasgrosman | 2022-07-25T17:57:25Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T17:57:14Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_accent_surpeninsular-0_nortepeninsular-10_s157
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
heriosousa/Reinforce-CartPole-v1 | heriosousa | 2022-07-25T17:56:44Z | 0 | 0 | null | [
"CartPole-v1",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
]
| reinforcement-learning | 2022-07-25T17:56:28Z | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-CartPole-v1
results:
- metrics:
- type: mean_reward
value: 459.10 +/- 75.15
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
---
# **Reinforce** Agent playing **CartPole-v1**
This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: https://github.com/huggingface/deep-rl-class/tree/main/unit5
|
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s463 | jonatasgrosman | 2022-07-25T17:52:19Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T17:52:08Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s463
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s362 | jonatasgrosman | 2022-07-25T17:47:23Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T17:47:11Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s362
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s240 | jonatasgrosman | 2022-07-25T17:42:12Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T17:42:00Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s240
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-8_female-2_s570 | jonatasgrosman | 2022-07-25T17:37:00Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T17:36:49Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_gender_male-8_female-2_s570
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-8_female-2_s322 | jonatasgrosman | 2022-07-25T17:32:14Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T17:32:03Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_gender_male-8_female-2_s322
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-2_female-8_s303 | jonatasgrosman | 2022-07-25T17:17:54Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T17:17:42Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_gender_male-2_female-8_s303
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-2_female-8_s201 | jonatasgrosman | 2022-07-25T17:13:02Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T17:12:50Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_gender_male-2_female-8_s201
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
psato/distilbert-base-uncased-finetuned-squad | psato | 2022-07-25T17:07:29Z | 5 | 0 | transformers | [
"transformers",
"pytorch",
"distilbert",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| question-answering | 2022-07-21T08:47:40Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: distilbert-base-uncased-finetuned-squad
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-squad
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the squad dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1552
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.2264 | 1.0 | 5533 | 1.1785 |
| 0.9409 | 2.0 | 11066 | 1.0934 |
| 0.7492 | 3.0 | 16599 | 1.1552 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
|
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-10_female-0_s682 | jonatasgrosman | 2022-07-25T17:03:49Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T17:03:37Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_gender_male-10_female-0_s682
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-10_female-0_s287 | jonatasgrosman | 2022-07-25T16:59:02Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T16:58:50Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_gender_male-10_female-0_s287
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-0_female-10_s895 | jonatasgrosman | 2022-07-25T16:54:07Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T16:53:56Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_gender_male-0_female-10_s895
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
MrSemyon12/wikineural-multilingual-ner-finetuned-ner | MrSemyon12 | 2022-07-25T16:40:32Z | 6 | 0 | transformers | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"token-classification",
"generated_from_trainer",
"dataset:skript",
"license:cc-by-nc-sa-4.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| token-classification | 2022-07-25T04:39:34Z | ---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- skript
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: wikineural-multilingual-ner-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: skript
type: skript
args: conll2003
metrics:
- name: Precision
type: precision
value: 0.9013505175841503
- name: Recall
type: recall
value: 0.9308318584070796
- name: F1
type: f1
value: 0.9158539983282251
- name: Accuracy
type: accuracy
value: 0.9658385093167702
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wikineural-multilingual-ner-finetuned-ner
This model is a fine-tuned version of [Babelscape/wikineural-multilingual-ner](https://huggingface.co/Babelscape/wikineural-multilingual-ner) on the skript dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1219
- Precision: 0.9014
- Recall: 0.9308
- F1: 0.9159
- Accuracy: 0.9658
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 298 | 0.1208 | 0.9016 | 0.8988 | 0.9002 | 0.9604 |
| 0.118 | 2.0 | 596 | 0.1152 | 0.9016 | 0.9210 | 0.9112 | 0.9645 |
| 0.118 | 3.0 | 894 | 0.1219 | 0.9014 | 0.9308 | 0.9159 | 0.9658 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
|
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-5_female-5_s73 | jonatasgrosman | 2022-07-25T16:39:30Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T16:39:19Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_gender_male-5_female-5_s73
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-5_female-5_s621 | jonatasgrosman | 2022-07-25T16:34:52Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T16:34:41Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_gender_male-5_female-5_s621
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-5_female-5_s544 | jonatasgrosman | 2022-07-25T16:30:07Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T16:29:53Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_gender_male-5_female-5_s544
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_xls-r_accent_us-8_england-2_s884 | jonatasgrosman | 2022-07-25T16:20:46Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T16:20:34Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_accent_us-8_england-2_s884
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_xls-r_accent_us-10_england-0_s947 | jonatasgrosman | 2022-07-25T15:55:08Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T15:54:56Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_accent_us-10_england-0_s947
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_xls-r_accent_us-10_england-0_s569 | jonatasgrosman | 2022-07-25T15:50:24Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T15:50:13Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_accent_us-10_england-0_s569
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_xls-r_accent_us-10_england-0_s253 | jonatasgrosman | 2022-07-25T15:45:51Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T15:45:38Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_accent_us-10_england-0_s253
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_xls-r_accent_us-5_england-5_s732 | jonatasgrosman | 2022-07-25T15:26:46Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T15:26:32Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_accent_us-5_england-5_s732
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
bigscience/bloom-optimizer-states | bigscience | 2022-07-25T15:19:06Z | 0 | 8 | null | [
"ak",
"ar",
"as",
"bm",
"bn",
"ca",
"code",
"en",
"es",
"eu",
"fon",
"fr",
"gu",
"hi",
"id",
"ig",
"ki",
"kn",
"lg",
"ln",
"ml",
"mr",
"ne",
"nso",
"ny",
"or",
"pa",
"pt",
"rn",
"rw",
"sn",
"st",
"sw",
"ta",
"te",
"tn",
"ts",
"tum",
"tw",
"ur",
"vi",
"wo",
"xh",
"yo",
"zh",
"zhs",
"zht",
"zu",
"arxiv:1909.08053",
"arxiv:2110.02861",
"arxiv:2108.12409",
"license:bigscience-bloom-rail-1.0",
"region:us"
]
| null | 2022-07-19T13:22:48Z | ---
license: bigscience-bloom-rail-1.0
language:
- ak
- ar
- as
- bm
- bn
- ca
- code
- en
- es
- eu
- fon
- fr
- gu
- hi
- id
- ig
- ki
- kn
- lg
- ln
- ml
- mr
- ne
- nso
- ny
- or
- pa
- pt
- rn
- rw
- sn
- st
- sw
- ta
- te
- tn
- ts
- tum
- tw
- ur
- vi
- wo
- xh
- yo
- zh
- zhs
- zht
- zu
---
# <span style="color:red"><b>WARNING:</b> The checkpoints on this repo corresponds to Megatron-Deespeed checkpoints. Use them together with our fork of [Megatron-DeepSpeed](https://github.com/bigscience-workshop/Megatron-DeepSpeed). For a normal Hugging Face Transformers checkpoint please go [here](https://huggingface.co/bigscience/bloom) instead. </span>
# <p>BLOOM LM<br/> _BigScience Large Open-science Open-access Multilingual Language Model_ <br/>Model Card</p>
<img src="https://assets.website-files.com/6139f3cdcbbff3a68486761d/613cd8997b270da063e230c5_Tekengebied%201-p-500.png" alt="BigScience Logo" width="200"/>
Version 1.0 / 20.July.2022 - Model card copied from [bloom-176-intermediate repo](https://huggingface.co/bigscience/bloom-176-intermediate)- Available intermediary checkpoints - global steps:
- **95000**
Request adding more checkpoints by adding an issue on this repo.
# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Training Data](#training-data)
4. [Risks and Limitations](#risks-and-limitations)
5. [Evaluation](#evaluation)
6. [Recommendations](#recommendations)
7. [Glossary and Calculations](#glossary-and-calculations)
8. [More Information](#more-information)
9. [Model Card Authors](#model-card-authors)
---
# Model Details
BLOOM is a type of language model, which is a probability distribution over sequences of words. Specifically, BLOOM is a Large Language Model (LLM), meaning that it is trained on vast amounts of text data using industrial-scale computational resources. As such, the model is able to capture the statistical tendencies of words, phrases, sentences, and larger spans of text that it is exposed to in the training data.
## Basics
*This section provides information about the model type, version, license, funders, release date, developers, and contact information.*
*It is useful for anyone who wants to reference the model.*
<details>
<summary>Click to expand</summary>
**Developed by:** BigScience ([website](https://bigscience.huggingface.co))
*All collaborators are either volunteers or have an agreement with their employer. (Further breakdown of participants forthcoming.)*
**Model Type:** Transformer-based Language Model
**Version:** 1.0.0
**Languages:** Multiple; see [training data](#training-data)
**License:** RAIL License v1.0 ([link](https://huggingface.co/spaces/bigscience/license))
**Release Date Estimate:** Monday, 11.July.2022
**Send Questions to:** [email protected]
**Cite as:** BigScience, _BigScience Language Open-science Open-access Multilingual (BLOOM) Language Model_. International, May 2021-May 2022
**Funded by:**
* The French government.
* Hugging Face ([website](https://huggingface.co)).
* Organizations of contributors. *(Further breakdown of organizations forthcoming.)*
</details>
## Technical Specifications
*This section includes details about the model objective and architecture, and the compute infrastructure.*
*It is useful for people interested in model development.*
<details>
<summary>Click to expand</summary>
Please see [the BLOOM training README](https://github.com/bigscience-workshop/bigscience/tree/master/train/tr11-176B-ml#readme) for full details on replicating training.
### Model Architecture and Objective
* Modified from Megatron-LM GPT2 (see [paper](https://arxiv.org/abs/1909.08053), [BLOOM Megatron code](https://github.com/bigscience-workshop/Megatron-DeepSpeed)):
* Decoder-only architecture
* Layer normalization applied to word embeddings layer (`StableEmbedding`; see [code](https://github.com/facebookresearch/bitsandbytes), [paper](https://arxiv.org/pdf/2110.02861.pdf))
* ALiBI positional encodings (see [paper](https://arxiv.org/pdf/2108.12409.pdf)), with GeLU activation functions
* 176 billion parameters:
* 70 layers, 112 attention heads
* Hidden layers are 14336-dimensional
* Sequence length of 2048 tokens used (see [BLOOM tokenizer](https://huggingface.co/bigscience/tokenizer), [tokenizer description](#tokenization))
**Objective Function:** Cross Entropy with mean reduction (see [API documentation](https://pytorch.org/docs/stable/generated/torch.nn.CrossEntropyLoss.html#torch.nn.CrossEntropyLoss)).
### Compute infrastructure
Jean Zay Public Supercomputer, provided by the French government (see [announcement](https://www.enseignementsup-recherche.gouv.fr/fr/signature-du-marche-d-acquisition-de-l-un-des-supercalculateurs-les-plus-puissants-d-europe-46733)).
#### Hardware
* 384 A100 80GB GPUs (48 nodes)
* Additional 32 A100 80GB GPUs (4 nodes) in reserve
* 8 GPUs per node Using NVLink 4 inter-gpu connects, 4 OmniPath links
* CPU: AMD
* CPU memory: 512GB per node
* GPU memory: 640GB per node
* Inter-node connect: Omni-Path Architecture (OPA)
* NCCL-communications network: a fully dedicated subnet
* Disc IO network: shared network with other types of nodes
#### Software
* Megatron-DeepSpeed ([Github link](https://github.com/bigscience-workshop/Megatron-DeepSpeed))
* DeepSpeed ([Github link](https://github.com/microsoft/DeepSpeed))
* PyTorch (pytorch-1.11 w/ CUDA-11.5; see [Github link](https://github.com/pytorch/pytorch))
* apex ([Github link](https://github.com/NVIDIA/apex))
</details>
---
# Training
*This section provides information about the training data, the speed and size of training elements, and the environmental impact of training.*
*It is useful for people who want to learn more about the model inputs and training footprint.*
<details>
<summary>Click to expand</summary>
## Training Data
*This section provides a high-level overview of the training data. It is relevant for anyone who wants to know the basics of what the model is learning.*
Details for each dataset are provided in individual [Data Cards](https://huggingface.co/spaces/bigscience/BigScienceCorpus).
Training data includes:
- 45 natural languages
- 12 programming languages
- In 1.5TB of pre-processed text, converted into 350B unique tokens (see [the tokenizer section](#tokenization) for more.)
### Languages
The pie chart shows the distribution of languages in training data.
The following tables shows the further distribution of Niger-Congo & Indic languages and programming languages in the training data.
Distribution of Niger Congo and Indic languages.
| Niger Congo | Percentage | | Indic | Percentage |
|----------------|------------ |------ |-----------|------------|
| Chi Tumbuka | 0.00002 | | Assamese | 0.01 |
| Kikuyu | 0.00004 | | Odia | 0.04 |
| Bambara | 0.00004 | | Gujarati | 0.04 |
| Akan | 0.00007 | | Marathi | 0.05 |
| Xitsonga | 0.00007 | | Punjabi | 0.05 |
| Sesotho | 0.00007 | | Kannada | 0.06 |
| Chi Chewa | 0.0001 | | Nepali | 0.07 |
| Setswana | 0.0002 | | Telugu | 0.09 |
| Northern Sotho | 0.0002 | | Malayalam | 0.10 |
| Fon | 0.0002 | | Urdu | 0.10 |
| Kirundi | 0.0003 | | Tamil | 0.20 |
| Wolof | 0.0004 | | Bengali | 0.50 |
| Kuganda | 0.0004 | | Hindi | 0.70 |
| Chi Shona | 0.001 |
| Isi Zulu | 0.001 |
| Igbo | 0.001 |
| Xhosa | 0.001 |
| Kinyarwanda | 0.003 |
| Yoruba | 0.006 |
| Swahili | 0.02 |
Distribution of programming languages.
| Extension | Language | Number of files |
|----------------|------------|-----------------|
| java | Java | 5,407,724 |
| php | PHP | 4,942,186 |
| cpp | C++ | 2,503,930 |
| py | Python | 2,435,072 |
| js | JavaScript | 1,905,518 |
| cs | C# | 1,577,347 |
| rb | Ruby | 6,78,413 |
| cc | C++ | 443,054 |
| hpp | C++ | 391,048 |
| lua | Lua | 352,317 |
| go | GO | 227,763 |
| ts | TypeScript | 195,254 |
| C | C | 134,537 |
| scala | Scala | 92,052 |
| hh | C++ | 67,161 |
| H | C++ | 55,899 |
| tsx | TypeScript | 33,107 |
| rs | Rust | 29,693 |
| phpt | PHP | 9,702 |
| c++ | C++ | 1,342 |
| h++ | C++ | 791 |
| php3 | PHP | 540 |
| phps | PHP | 270 |
| php5 | PHP | 166 |
| php4 | PHP | 29 |
### Preprocessing
**Tokenization:** The BLOOM tokenizer ([link](https://huggingface.co/bigscience/tokenizer)), a learned subword tokenizer trained using:
- A byte-level Byte Pair Encoding (BPE) algorithm
- A simple pre-tokenization rule, no normalization
- A vocabulary size of 250,680
It was trained on a subset of a preliminary version of the corpus using alpha-weighting per language.
## Speeds, Sizes, Times
Training logs: [Tensorboard link](https://huggingface.co/tensorboard/bigscience/tr11-176B-ml-logs/)
- Dates:
- Started 11th March, 2022 11:42am PST
- Estimated end: 5th July, 2022
- Checkpoint size:
- Bf16 weights: 329GB
- Full checkpoint with optimizer states: 2.3TB
- Training throughput: About 150 TFLOP per GPU per second
- Number of epochs: 1
- Estimated cost of training: Equivalent of $2-5M in cloud computing (including preliminary experiments)
- Server training location: Île-de-France, France
## Environmental Impact
The training supercomputer, Jean Zay ([website](http://www.idris.fr/eng/jean-zay/jean-zay-presentation-eng.html)), uses mostly nuclear energy. The heat generated by it is reused for heating campus housing.
**Estimated carbon emissions:** *(Forthcoming.)*
**Estimated electricity usage:** *(Forthcoming.)*
</details>
---
# Uses
*This section addresses questions around how the model is intended to be used, discusses the foreseeable users of the model (including those affected by the model), and describes uses that are considered out of scope or misuse of the model.*
*It is useful for anyone considering using the model or who is affected by the model.*
<details>
<summary>Click to expand</summary>
## Intended Use
This model is being created in order to enable public research on large language models (LLMs). LLMs are intended to be used for language generation or as a pretrained base model that can be further fine-tuned for specific tasks. Use cases below are not exhaustive.
### Direct Use
- Text generation
- Exploring characteristics of language generated by a language model
- Examples: Cloze tests, counterfactuals, generations with reframings
### Downstream Use
- Tasks that leverage language models include: Information Extraction, Question Answering, Summarization
### Misuse and Out-of-scope Use
*This section addresses what users ought not do with the model.*
See the [BLOOM License](https://huggingface.co/spaces/bigscience/license), Attachment A, for detailed usage restrictions. The below list is non-exhaustive, but lists some easily foreseeable problematic use cases.
#### Out-of-scope Uses
Using the model in [high-stakes](#high-stakes) settings is out of scope for this model. The model is not designed for [critical decisions](#critical-decisions) nor uses with any material consequences on an individual's livelihood or wellbeing. The model outputs content that appears factual but is not correct.
Out-of-scope Uses Include:
- Usage in biomedical domains, political and legal domains, or finance domains
- Usage for evaluating or scoring individuals, such as for employment, education, or credit
- Applying the model for critical automatic decisions, generating factual content, creating reliable summaries, or generating predictions that must be correct
#### Misuse
Intentionally using the model for harm, violating [human rights](#human-rights), or other kinds of malicious activities, is a misuse of this model. This includes:
- Spam generation
- Disinformation and influence operations
- Disparagement and defamation
- Harassment and abuse
- [Deception](#deception)
- Unconsented impersonation and imitation
- Unconsented surveillance
- Generating content without attribution to the model, as specified in the [RAIL License, Use Restrictions](https://huggingface.co/spaces/bigscience/license)
## Intended Users
### Direct Users
- General Public
- Researchers
- Students
- Educators
- Engineers/developers
- Non-commercial entities
- Community advocates, including human and civil rights groups
### Indirect Users
- Users of derivatives created by Direct Users, such as those using software with an [intended use](#intended-use)
- Users of [Derivatives of the Model, as described in the License](https://huggingface.co/spaces/bigscience/license)
### Others Affected (Parties Prenantes)
- People and groups referred to by the LLM
- People and groups exposed to outputs of, or decisions based on, the LLM
- People and groups whose original work is included in the LLM
</details>
---
# Risks and Limitations
*This section identifies foreseeable harms and misunderstandings.*
<details>
<summary>Click to expand</summary>
Model may:
- Overrepresent some viewpoints and underrepresent others
- Contain stereotypes
- Contain [personal information](#personal-data-and-information)
- Generate:
- Hateful, abusive, or violent language
- Discriminatory or prejudicial language
- Content that may not be appropriate for all settings, including sexual content
- Make errors, including producing incorrect information as if it were factual
- Generate irrelevant or repetitive outputs
</details>
---
# Evaluation
*This section describes the evaluation protocols and provides the results.*
<details>
<summary>Click to expand</summary>
## Metrics
*This section describes the different ways performance is calculated and why.*
Includes:
| Metric | Why chosen |
|--------------------|--------------------------------------------------------------------|
| [Perplexity](#perplexity) | Standard metric for quantifying model improvements during training |
| Cross Entropy [Loss](#loss) | Standard objective for language models. |
And multiple different metrics for specific tasks. _(More evaluation metrics forthcoming upon completion of evaluation protocol.)_
## Factors
*This section lists some different aspects of what BLOOM models. Its focus is on those aspects that are likely to give rise to high variance in model behavior.*
- Language, such as English or Yoruba
- Domain, such as newswire or stories
- Demographic characteristics, such as gender or nationality
## Results
*Results are based on the [Factors](#factors) and [Metrics](#metrics).*
**Train-time Evaluation:**
As of 25.May.2022, 15:00 PST:
- Training Loss: 2.0
- Validation Loss: 2.2
- Perplexity: 8.9
(More evaluation scores forthcoming.)
</details>
---
# Recommendations
*This section provides information on warnings and potential mitigations.*
<details>
<summary>Click to expand</summary>
- Indirect users should be made aware when the content they're working with is created by the LLM.
- Users should be aware of [Risks and Limitations](#risks-and-limitations), and include an appropriate age disclaimer or blocking interface as necessary.
- Models trained or finetuned downstream of BLOOM LM should include an updated Model Card.
- Users of the model should provide mechanisms for those affected to provide feedback, such as an email address for comments.
</details>
---
# Glossary and Calculations
*This section defines common terms and how metrics are calculated.*
<details>
<summary>Click to expand</summary>
- <a name="loss">**Loss:**</a> A calculation of the difference between what the model has learned and what the data shows ("groundtruth"). The lower the loss, the better. The training process aims to minimize the loss.
- <a name="perplexity">**Perplexity:**</a> This is based on what the model estimates the probability of new data is. The lower the perplexity, the better. If the model is 100% correct at predicting the next token it will see, then the perplexity is 1. Mathematically this is calculated using entropy.
- <a name="high-stakes">**High-stakes settings:**</a> Such as those identified as "high-risk AI systems" and "unacceptable risk AI systems" in the European Union's proposed [Artificial Intelligence (AI) Act](https://artificialintelligenceact.eu/annexes/).
- <a name="critical-decisions">**Critical decisions:**</a> Such as those defined in [the United States' proposed Algorithmic Accountability Act](https://www.congress.gov/117/bills/s3572/BILLS-117s3572is.pdf).
- <a name="human-rights">**Human rights:**</a> Includes those rights defined in the [Universal Declaration of Human Rights](https://www.un.org/sites/un2.un.org/files/2021/03/udhr.pdf).
- <a name="personal-data-and-information">**Personal Data and Personal Information:**</a> Personal data and information is defined in multiple data protection regulations, such as "[personal data](https://gdpr-info.eu/issues/personal-data/)" in the [European Union's General Data Protection Regulation](https://gdpr-info.eu); and "personal information" in the Republic of South Africa's [Protection of Personal Information Act](https://www.gov.za/sites/default/files/gcis_document/201409/3706726-11act4of2013popi.pdf), The People's Republic of China's [Personal information protection law](http://en.npc.gov.cn.cdurl.cn/2021-12/29/c_694559.htm).
- <a name="sensitive-characteristics">**Sensitive characteristics:**</a> This includes specifically protected categories in human rights (see [UHDR, Article 2](https://www.un.org/sites/un2.un.org/files/2021/03/udhr.pdf)) and personal information regulation (see GDPR, [Article 9; Protection of Personal Information Act, Chapter 1](https://www.gov.za/sites/default/files/gcis_document/201409/3706726-11act4of2013popi.pdf))
- <a name="deception">**Deception:**</a> Doing something to intentionally mislead individuals to believe something that is false, such as by creating deadbots or chatbots on social media posing as real people, or generating text documents without making consumers aware that the text is machine generated.
</details>
---
# More Information
*This section provides links to writing on dataset creation, technical specifications, lessons learned, and initial results.*
<details>
<summary>Click to expand</summary>
## Dataset Creation
Blog post detailing the design choices during the dataset creation: https://bigscience.huggingface.co/blog/building-a-tb-scale-multilingual-dataset-for-language-modeling
## Technical Specifications
Blog post summarizing how the architecture, size, shape, and pre-training duration where selected: https://bigscience.huggingface.co/blog/what-language-model-to-train-if-you-have-two-million-gpu-hours
More details on the architecture/optimizer: https://github.com/bigscience-workshop/bigscience/tree/master/train/tr11-176B-ml
Blog post on the hardware/engineering side: https://bigscience.huggingface.co/blog/which-hardware-to-train-a-176b-parameters-model
Details on the distributed setup used for the training: https://github.com/bigscience-workshop/bigscience/tree/master/train/tr11-176B-ml
Tensorboard updated during the training: https://huggingface.co/bigscience/tr11-176B-ml-logs/tensorboard#scalars&tagFilter=loss
## Lessons
Insights on how to approach training, negative results: https://github.com/bigscience-workshop/bigscience/blob/master/train/lessons-learned.md
Details on the obstacles overcome during the preparation on the engineering side (instabilities, optimization of training throughput, so many technical tricks and questions): https://github.com/bigscience-workshop/bigscience/blob/master/train/tr11-176B-ml/chronicles.md
## Initial Results
Initial prompting experiments using interim checkpoints: https://huggingface.co/spaces/bigscience/bloom-book
</details>
---
# Model Card Authors
*Ordered roughly chronologically and by amount of time spent.*
Margaret Mitchell, Giada Pistilli, Yacine Jernite, Ezinwanne Ozoani, Marissa Gerchick, Nazneen Rajani, Sasha Luccioni, Irene Solaiman, Maraim Masoud, Somaieh Nikpoor, Carlos Muñoz Ferrandis, Stas Bekman, Christopher Akiki, Danish Contractor, David Lansky, Angelina McMillan-Major, Tristan Thrush, Suzana Ilić, Gérard Dupont, Shayne Longpre, Manan Dey, Stella Biderman, Douwe Kiela, Emi Baylor, Teven Le Scao, Aaron Gokaslan, Julien Launay |
jonatasgrosman/exp_w2v2r_en_xls-r_accent_us-5_england-5_s334 | jonatasgrosman | 2022-07-25T15:17:39Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T15:17:28Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_xls-r_accent_us-5_england-5_s334
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_de_xls-r_gender_male-8_female-2_s949 | jonatasgrosman | 2022-07-25T15:12:21Z | 4 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T15:12:06Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_gender_male-8_female-2_s949
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_de_xls-r_gender_male-8_female-2_s293 | jonatasgrosman | 2022-07-25T15:07:36Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T15:07:22Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_gender_male-8_female-2_s293
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
venturaville/xlm-roberta-base-finetuned-panx-de | venturaville | 2022-07-25T15:02:55Z | 4 | 0 | transformers | [
"transformers",
"pytorch",
"tensorboard",
"xlm-roberta",
"token-classification",
"generated_from_trainer",
"dataset:xtreme",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| token-classification | 2022-07-05T21:21:27Z | ---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-de
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.de
metrics:
- name: F1
type: f1
value: 0.8632527372262775
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-de
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1367
- F1: 0.8633
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2582 | 1.0 | 525 | 0.1653 | 0.8238 |
| 0.1301 | 2.0 | 1050 | 0.1417 | 0.8439 |
| 0.0841 | 3.0 | 1575 | 0.1367 | 0.8633 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.11.0+cu102
- Datasets 1.16.1
- Tokenizers 0.10.3
|
RajSang/q-FrozenLake-v1-4x4-noSlippery | RajSang | 2022-07-25T14:53:19Z | 0 | 0 | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
]
| reinforcement-learning | 2022-07-25T14:53:11Z | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- metrics:
- type: mean_reward
value: 1.00 +/- 0.00
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: FrozenLake-v1-4x4-no_slippery
---
# **Q-Learning** Agent playing **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="RajSang/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
evaluate_agent(env, model["max_steps"], model["n_eval_episodes"], model["qtable"], model["eval_seed"])
```
|
seeksery/DialoGPT-calig | seeksery | 2022-07-25T14:47:41Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
]
| text-generation | 2022-07-25T13:26:43Z | ---
tags:
- conversational
---
|
jonatasgrosman/exp_w2v2r_de_xls-r_gender_male-10_female-0_s598 | jonatasgrosman | 2022-07-25T14:43:18Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T14:43:04Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_gender_male-10_female-0_s598
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_de_xls-r_gender_male-10_female-0_s119 | jonatasgrosman | 2022-07-25T14:34:01Z | 4 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T14:33:49Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_gender_male-10_female-0_s119
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_de_xls-r_gender_male-0_female-10_s922 | jonatasgrosman | 2022-07-25T14:29:29Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T14:29:18Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_gender_male-0_female-10_s922
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_de_xls-r_gender_male-0_female-10_s867 | jonatasgrosman | 2022-07-25T14:24:56Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T14:24:45Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_gender_male-0_female-10_s867
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_de_xls-r_gender_male-5_female-5_s896 | jonatasgrosman | 2022-07-25T14:15:40Z | 4 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T14:15:29Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_gender_male-5_female-5_s896
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_de_xls-r_gender_male-5_female-5_s719 | jonatasgrosman | 2022-07-25T14:10:54Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T14:10:43Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_gender_male-5_female-5_s719
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_de_xls-r_gender_male-5_female-5_s336 | jonatasgrosman | 2022-07-25T14:05:48Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T14:05:37Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_gender_male-5_female-5_s336
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_de_xls-r_accent_germany-2_austria-8_s543 | jonatasgrosman | 2022-07-25T13:46:09Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T13:45:58Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_accent_germany-2_austria-8_s543
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_de_xls-r_accent_germany-2_austria-8_s368 | jonatasgrosman | 2022-07-25T13:36:22Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T13:35:55Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_accent_germany-2_austria-8_s368
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_de_xls-r_accent_germany-10_austria-0_s886 | jonatasgrosman | 2022-07-25T13:31:32Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T13:31:20Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_accent_germany-10_austria-0_s886
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
benjamyu/autotrain-ms-2-1174443640 | benjamyu | 2022-07-25T13:26:05Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"autotrain",
"en",
"dataset:benjamyu/autotrain-data-ms-2",
"co2_eq_emissions",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
]
| text2text-generation | 2022-07-25T03:54:44Z | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- benjamyu/autotrain-data-ms-2
co2_eq_emissions: 4.619328856849087
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1174443640
- CO2 Emissions (in grams): 4.619328856849087
## Validation Metrics
- Loss: 2.689530849456787
- Rouge1: 15.9713
- Rouge2: 2.1067
- RougeL: 12.1778
- RougeLsum: 13.5772
- Gen Len: 18.9798
## Usage
You can use cURL to access this model:
```
$ curl -X POST -H "Authorization: Bearer YOUR_HUGGINGFACE_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/benjamyu/autotrain-ms-2-1174443640
``` |
mtreviso/ct5-small-en-wiki-l2r | mtreviso | 2022-07-25T13:22:55Z | 22 | 0 | transformers | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"en",
"dataset:wikipedia",
"license:afl-3.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
]
| text2text-generation | 2022-07-17T04:48:26Z | ---
license: afl-3.0
language: en
tags:
- t5
datasets:
- wikipedia
---
# cT5-small left-to-right
Github: https://github.com/mtreviso/chunked-t5
This is a variant of [cT5](https://huggingface.co/mtreviso/ct5-small-en-wiki) that was trained with a left-to-right autoregressive decoding mask. As a consequence, it does not support parallel decoding, but it still predicts the end-of-chunk token `</c>` at the end of each chunk. |
jonatasgrosman/exp_w2v2r_de_xls-r_accent_germany-10_austria-0_s295 | jonatasgrosman | 2022-07-25T13:22:00Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T13:21:49Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_accent_germany-10_austria-0_s295
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_de_xls-r_accent_germany-0_austria-10_s381 | jonatasgrosman | 2022-07-25T13:12:15Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T13:12:04Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_accent_germany-0_austria-10_s381
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_de_xls-r_accent_germany-5_austria-5_s534 | jonatasgrosman | 2022-07-25T12:57:24Z | 4 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T12:57:06Z | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_de_xls-r_accent_germany-5_austria-5_s534
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_gender_male-8_female-2_s911 | jonatasgrosman | 2022-07-25T12:47:42Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T12:47:31Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_gender_male-8_female-2_s911
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_gender_male-8_female-2_s500 | jonatasgrosman | 2022-07-25T12:43:00Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T12:42:49Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_gender_male-8_female-2_s500
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_gender_male-2_female-8_s3 | jonatasgrosman | 2022-07-25T11:58:32Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T11:58:21Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_gender_male-2_female-8_s3
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_gender_male-2_female-8_s255 | jonatasgrosman | 2022-07-25T11:54:01Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T11:53:50Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_gender_male-2_female-8_s255
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_gender_male-10_female-0_s714 | jonatasgrosman | 2022-07-25T11:49:14Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T11:48:54Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_gender_male-10_female-0_s714
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_gender_male-10_female-0_s626 | jonatasgrosman | 2022-07-25T11:41:49Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T11:41:37Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_gender_male-10_female-0_s626
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_gender_male-0_female-10_s934 | jonatasgrosman | 2022-07-25T11:31:25Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T11:31:13Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_gender_male-0_female-10_s934
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_gender_male-0_female-10_s469 | jonatasgrosman | 2022-07-25T11:26:43Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T11:26:32Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_gender_male-0_female-10_s469
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
huggingtweets/bwahwtfbwah | huggingtweets | 2022-07-25T11:22:47Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
]
| text-generation | 2022-07-25T11:21:28Z | ---
language: en
thumbnail: http://www.huggingtweets.com/bwahwtfbwah/1658748163123/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1543387213370638338/Xn8bL7wJ_400x400.jpg')">
</div>
<div
style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('')">
</div>
<div
style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('')">
</div>
</div>
<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI BOT 🤖</div>
<div style="text-align: center; font-size: 16px; font-weight: 800">🤍🖤</div>
<div style="text-align: center; font-size: 14px;">@bwahwtfbwah</div>
</div>
I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
Create your own bot based on your favorite user with [the demo](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb)!
## How does it work?
The model uses the following pipeline.
To understand how the model was developed, check the [W&B report](https://wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-Model-to-Generate-Tweets--VmlldzoxMTY5MjI).
## Training data
The model was trained on tweets from 🤍🖤.
| Data | 🤍🖤 |
| --- | --- |
| Tweets downloaded | 3245 |
| Retweets | 501 |
| Short tweets | 655 |
| Tweets kept | 2089 |
[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/p4n65kie/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
## Training procedure
The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @bwahwtfbwah's tweets.
Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3pyxv8zk) for full transparency and reproducibility.
At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3pyxv8zk/artifacts) is logged and versioned.
## How to use
You can use this model directly with a pipeline for text generation:
```python
from transformers import pipeline
generator = pipeline('text-generation',
model='huggingtweets/bwahwtfbwah')
generator("My dream is", num_return_sequences=5)
```
## Limitations and bias
The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).
In addition, the data present in the user's tweets further affects the text generated by the model.
## About
*Built by Boris Dayma*
[](https://twitter.com/intent/follow?screen_name=borisdayma)
For more details, visit the project repository.
[](https://github.com/borisdayma/huggingtweets)
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_gender_male-0_female-10_s400 | jonatasgrosman | 2022-07-25T11:22:02Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T11:21:49Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_gender_male-0_female-10_s400
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_gender_male-5_female-5_s722 | jonatasgrosman | 2022-07-25T11:17:28Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T11:17:17Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_gender_male-5_female-5_s722
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_gender_male-5_female-5_s474 | jonatasgrosman | 2022-07-25T11:12:28Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T11:12:15Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_gender_male-5_female-5_s474
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_accent_france-2_belgium-8_s709 | jonatasgrosman | 2022-07-25T10:48:54Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T10:48:42Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_accent_france-2_belgium-8_s709
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_accent_france-2_belgium-8_s204 | jonatasgrosman | 2022-07-25T10:39:13Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T10:38:56Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_accent_france-2_belgium-8_s204
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_accent_france-10_belgium-0_s869 | jonatasgrosman | 2022-07-25T10:34:28Z | 4 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T10:34:13Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_accent_france-10_belgium-0_s869
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_accent_france-10_belgium-0_s396 | jonatasgrosman | 2022-07-25T10:29:31Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T10:29:20Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_accent_france-10_belgium-0_s396
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_accent_france-10_belgium-0_s271 | jonatasgrosman | 2022-07-25T10:24:53Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T10:24:41Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_accent_france-10_belgium-0_s271
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_accent_france-0_belgium-10_s290 | jonatasgrosman | 2022-07-25T10:08:18Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T10:08:06Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_accent_france-0_belgium-10_s290
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_accent_france-5_belgium-5_s607 | jonatasgrosman | 2022-07-25T10:03:24Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T10:03:13Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_accent_france-5_belgium-5_s607
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_fr_vp-100k_accent_france-5_belgium-5_s244 | jonatasgrosman | 2022-07-25T09:52:06Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T09:51:55Z | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_fr_vp-100k_accent_france-5_belgium-5_s244
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_gender_male-2_female-8_s821 | jonatasgrosman | 2022-07-25T09:32:09Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T09:31:57Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_gender_male-2_female-8_s821
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_gender_male-2_female-8_s579 | jonatasgrosman | 2022-07-25T09:27:15Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T09:27:03Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_gender_male-2_female-8_s579
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_gender_male-2_female-8_s557 | jonatasgrosman | 2022-07-25T09:22:31Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T09:22:16Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_gender_male-2_female-8_s557
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_gender_male-10_female-0_s784 | jonatasgrosman | 2022-07-25T09:17:51Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T09:17:40Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_gender_male-10_female-0_s784
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_gender_male-10_female-0_s246 | jonatasgrosman | 2022-07-25T09:13:05Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T09:12:53Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_gender_male-10_female-0_s246
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_gender_male-0_female-10_s878 | jonatasgrosman | 2022-07-25T09:03:39Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T09:03:23Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_gender_male-0_female-10_s878
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_gender_male-0_female-10_s496 | jonatasgrosman | 2022-07-25T08:58:17Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T08:58:04Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_gender_male-0_female-10_s496
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_gender_male-5_female-5_s966 | jonatasgrosman | 2022-07-25T08:48:50Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T08:48:38Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_gender_male-5_female-5_s966
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_accent_surpeninsular-8_nortepeninsular-2_s149 | jonatasgrosman | 2022-07-25T08:29:17Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T08:29:02Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_accent_surpeninsular-8_nortepeninsular-2_s149
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_accent_surpeninsular-2_nortepeninsular-8_s578 | jonatasgrosman | 2022-07-25T08:14:41Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T08:14:29Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_accent_surpeninsular-2_nortepeninsular-8_s578
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_accent_surpeninsular-2_nortepeninsular-8_s317 | jonatasgrosman | 2022-07-25T08:09:59Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T08:09:46Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_accent_surpeninsular-2_nortepeninsular-8_s317
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_accent_surpeninsular-10_nortepeninsular-0_s335 | jonatasgrosman | 2022-07-25T08:05:21Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T08:05:07Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_accent_surpeninsular-10_nortepeninsular-0_s335
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_accent_surpeninsular-10_nortepeninsular-0_s27 | jonatasgrosman | 2022-07-25T08:00:18Z | 4 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T08:00:07Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_accent_surpeninsular-10_nortepeninsular-0_s27
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_accent_surpeninsular-10_nortepeninsular-0_s222 | jonatasgrosman | 2022-07-25T07:55:31Z | 5 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T07:55:20Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_accent_surpeninsular-10_nortepeninsular-0_s222
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_accent_surpeninsular-0_nortepeninsular-10_s692 | jonatasgrosman | 2022-07-25T07:50:51Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T07:50:40Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_accent_surpeninsular-0_nortepeninsular-10_s692
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_es_vp-100k_accent_surpeninsular-5_nortepeninsular-5_s965 | jonatasgrosman | 2022-07-25T07:33:45Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T07:33:33Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_accent_surpeninsular-5_nortepeninsular-5_s965
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
nlp-esg-scoring/bert-base-finetuned-esg-TCFD-clean | nlp-esg-scoring | 2022-07-25T07:29:45Z | 4 | 0 | transformers | [
"transformers",
"tf",
"bert",
"fill-mask",
"generated_from_keras_callback",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| fill-mask | 2022-07-25T01:48:03Z | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: nlp-esg-scoring/bert-base-finetuned-esg-TCFD-clean
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# nlp-esg-scoring/bert-base-finetuned-esg-TCFD-clean
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 2.7816
- Validation Loss: 2.3592
- Epoch: 9
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -571, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 2.7776 | 2.3647 | 0 |
| 2.7744 | 2.3469 | 1 |
| 2.7683 | 2.3527 | 2 |
| 2.7743 | 2.3708 | 3 |
| 2.7809 | 2.3819 | 4 |
| 2.7674 | 2.3599 | 5 |
| 2.7715 | 2.3541 | 6 |
| 2.7766 | 2.3423 | 7 |
| 2.7834 | 2.3535 | 8 |
| 2.7816 | 2.3592 | 9 |
### Framework versions
- Transformers 4.20.1
- TensorFlow 2.8.2
- Datasets 2.3.2
- Tokenizers 0.12.1
|
jonatasgrosman/exp_w2v2r_es_vp-100k_accent_surpeninsular-5_nortepeninsular-5_s411 | jonatasgrosman | 2022-07-25T07:29:05Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T07:28:54Z | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_es_vp-100k_accent_surpeninsular-5_nortepeninsular-5_s411
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2r_en_vp-100k_gender_male-8_female-2_s515 | jonatasgrosman | 2022-07-25T07:13:08Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T07:12:55Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_vp-100k_gender_male-8_female-2_s515
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
hassan4830/xlm-roberta-base-finetuned-urdu | hassan4830 | 2022-07-25T07:09:45Z | 45 | 8 | transformers | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"ur",
"license:afl-3.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
]
| text-classification | 2022-07-20T16:23:36Z | ---
language: ur
license: afl-3.0
---
# XLM-RoBERTa-Urdu-Classification
This [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) text classification model trained on Urdu sentiment [data-set](https://huggingface.co/datasets/hassan4830/urdu-binary-classification-data) performs binary sentiment classification on any given Urdu sentence. The model has been fine-tuned for better results in manageable time frames.
## Model description
XLM-RoBERTa is a scaled cross-lingual sentence encoder. It is trained on 2.5T of data across 100 languages data filtered from Common Crawl. XLM-R achieves state-of-the-arts results on multiple cross-lingual benchmarks.
The XLM-RoBERTa model was proposed in Unsupervised Cross-lingual Representation Learning at Scale by Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov.
It is based on Facebook’s RoBERTa model released in 2019. It is a large multi-lingual language model, trained on 2.5TB of filtered CommonCrawl data.
### How to use
You can import this model directly from the transformers library:
```python
>>> from transformers import AutoTokenizer, AutoModelForSequenceClassification
>>> tokenizer = AutoTokenizer.from_pretrained("hassan4830/xlm-roberta-base-finetuned-urdu")
>>> model = AutoModelForSequenceClassification.from_pretrained("hassan4830/xlm-roberta-base-finetuned-urdu")
```
Here is how to use this model to get the label of a given text:
```python
>>> from transformers import TextClassificationPipeline
>>> text = "وہ ایک برا شخص ہے"
>>> pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer, return_all_scores=True, device = 0)
>>> pipe(text)
```
|
jonatasgrosman/exp_w2v2r_en_vp-100k_gender_male-8_female-2_s250 | jonatasgrosman | 2022-07-25T07:08:25Z | 3 | 0 | transformers | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
]
| automatic-speech-recognition | 2022-07-25T07:08:14Z | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2r_en_vp-100k_gender_male-8_female-2_s250
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
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