Menlo
/

Speechless-llama3.2-v0.1

@@ -1,199 +1,100 @@
 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-## Uses
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-### Direct Use
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-[More Information Needed]
-### Downstream Use [optional]
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-[More Information Needed]
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-[More Information Needed]
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-[More Information Needed]
-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-## How to Get Started with the Model
-Use the code below to get started with the model.
-[More Information Needed]
-## Training Details
-### Training Data
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-[More Information Needed]
-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-#### Preprocessing [optional]
-[More Information Needed]
-#### Training Hyperparameters
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-#### Speeds, Sizes, Times [optional]
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-[More Information Needed]
 ## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
-### Testing Data, Factors & Metrics
-#### Testing Data
-<!-- This should link to a Dataset Card if possible. -->
-[More Information Needed]
-#### Factors
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-[More Information Needed]
-#### Metrics
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-[More Information Needed]
-### Results
-[More Information Needed]
-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
-[More Information Needed]
-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-## Technical Specifications [optional]
-### Model Architecture and Objective
-[More Information Needed]
-### Compute Infrastructure
-[More Information Needed]
-#### Hardware
-[More Information Needed]
-#### Software
-[More Information Needed]
-## Citation [optional]
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 **BibTeX:**
-[More Information Needed]
-**APA:**
-[More Information Needed]
-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Model Card Authors [optional]
-[More Information Needed]
-## Model Card Contact
-[More Information Needed]

 ---
+datasets:
+- homebrewltd/Ichigo-tokenized-v0.1
+language:
+- en
+- vi
+license: apache-2.0
+tags:
+- sound language model
+- audio-text-to-text
+- torchtune
+- whisperspeech
 ---
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65713d70f56f9538679e5a56/BjNGSPCF5z-tp9aAGsZN9.png)
+## Speechless
+Speechless is a compact, open-source text-to-semantics (1B parameters) model, designed to generate direct semantic representations of audio as discrete tokens, bypassing the need for a text-to-speech (TTS) model. Unlike traditional pipelines that rely on generating and processing audio (TTS → ASR), Speechless eliminates this complexity by directly converting text into semantic speech tokens, simplifying training, saving resources, and enabling scalability, especially for low-resource languages.
+Trained on over XXX hours of English and XXX hours of Vietnamese data, Speechless is a core component of the Ichigo v0.5 family.
+For more details, check out our official [blog post]().
+### Model Summary
+**Developed by:** Homebrew Research.
+**Model Architecture:** Llama
+**Model type:** Text to Semantics
+**Language(s):** English and Vietnamese
+**License:** Apache 2.0
+### Resources
+**Blog:** [Blog post]()
+## Intended Use
+**Intended Use Cases** This model is primarily designed for research purposes. This version focuses on generating direct semantic representations of audio as discrete tokens, eliminating the need for a text-to-speech (TTS) model.
+**Out-of-scope** The use of Ichigo Whisper in any manner that violates applicable laws or regulations is strictly prohibited.
+## How to Get Started
+You can use given example code to load the model.
+```{python}
+```
+## Training Specs
+| **Parameter**              | **Value**               |
+|----------------------------|-------------------------|
+| **Epochs**                 |                         |
+| **Global Batch Size**      |                         |
+| **Learning Rate**          |                         |
+| **Learning Scheduler**     | Cosine                  |
+| **Optimizer**              | AdamW                   |
+| **Warmup Ratio**           |                         |
+| **Weight Decay**           |                         |
+| **Max Sequence Length**    |                         |
 ## Evaluation
+1. Vietnamese
+| Model Name | Dataset test | Test samples | WER |
+|------------|--------------|--------------|-----|
+| **Speechless v0.1** | viet_bud500 | 7500 | **3.99** |
+2. English
+| Model Name | Dataset test | Test samples | WER |
+|------------|--------------|--------------|-----|
+| **Speechless v0.1** | librispeech_asr | 2620 | **3.27** |
+## Citation Information
 **BibTeX:**
+```
+@article{Speechless 2024,
+  title={Speechless},
+  author={Homebrew Research},
+  year=2024,
+  month=December},
+  url={https://huggingface.co/homebrewltd/Speechless-llama3.2-v0.1}
+```
+## Acknowledgement
+- **[WhisperSpeech](https://github.com/collabora/WhisperSpeech)**
+- **[Llama3.2](https://huggingface.co/meta-llama/Meta-Llama-3.2-1B-Base)**