
## RoBERTa in Swahili

This model was trained using HuggingFace's Flax framework and is part of the [JAX/Flax Community Week](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104) organized by [HuggingFace](https://huggingface.co). All training was done on a TPUv3-8 VM sponsored by the Google Cloud team.

## How to use

```python
from transformers import AutoTokenizer, AutoModelForMaskedLM
  
tokenizer = AutoTokenizer.from_pretrained("flax-community/roberta-swahili")

model = AutoModelForMaskedLM.from_pretrained("flax-community/roberta-swahili")

print(round((model.num_parameters())/(1000*1000)),"Million Parameters")

105 Million Parameters
```

#### **Training Data**:
This model was trained on [Swahili Safi](https://huggingface.co/datasets/flax-community/swahili-safi)

#### **Results**:
[MasakhaNER](https://github.com/masakhane-io/masakhane-ner) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1OIurb4J91X7461NQXLCCGzjeEGJq_Tyl?usp=sharing)


```
Eval metrics: {'f1': 86%}
```
This [model](https://huggingface.co/flax-community/roberta-swahili-news-classification) was fine-tuned based off this model for the
[Zindi News Classification Challenge](https://zindi.africa/hackathons/ai4d-swahili-news-classification-challenge)


#### **More Details**:
For more details and Demo please check [HF Swahili Space](https://huggingface.co/spaces/flax-community/Swahili)

{"language": "sw", "datasets": ["flax-community/swahili-safi"], "widget": [{"text": "Si kila mwenye makucha <mask> simba."}]}
transformers pytorch jax tensorboard roberta fill-mask sw dataset:flax-community/swahili-safi autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #jax #tensorboard #roberta #fill-mask #sw #dataset-flax-community/swahili-safi #autotrain_compatible #endpoints_compatible #has_space #region-us 


## RoBERTa in Swahili

This model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community Week organized by HuggingFace. All training was done on a TPUv3-8 VM sponsored by the Google Cloud team.

## How to use



#### Training Data:
This model was trained on Swahili Safi

#### Results:
MasakhaNER ![Open In Colab](URL



This model was fine-tuned based off this model for the
Zindi News Classification Challenge


#### More Details:
For more details and Demo please check HF Swahili Space

## RoBERTa in Swahili

This model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community Week organized by HuggingFace. All training was done on a TPUv3-8 VM sponsored by the Google Cloud team. ## How to use #### Training Data:
This model was trained on Swahili Safi #### Results:
MasakhaNER ![Open In Colab](URL



This model was fine-tuned based off this model for the
Zindi News Classification Challenge #### More Details:
For more details and Demo please check HF Swahili Space
TAGS
#transformers #pytorch #jax #tensorboard #roberta #fill-mask #sw #dataset-flax-community/swahili-safi #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ## RoBERTa in Swahili

This model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community Week organized by HuggingFace. All training was done on a TPUv3-8 VM sponsored by the Google Cloud team. ## How to use #### Training Data:
This model was trained on Swahili Safi #### Results:
MasakhaNER ![Open In Colab](URL



This model was fine-tuned based off this model for the
Zindi News Classification Challenge #### More Details:
For more details and Demo please check HF Swahili Space
passage: TAGS
#transformers #pytorch #jax #tensorboard #roberta #fill-mask #sw #dataset-flax-community/swahili-safi #autotrain_compatible #endpoints_compatible #has_space #region-us 
## RoBERTa in Swahili

This model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community Week organized by HuggingFace. All training was done on a TPUv3-8 VM sponsored by the Google Cloud team.## How to use#### Training Data:
This model was trained on Swahili Safi#### Results:
MasakhaNER ![Open In Colab](URL



This model was fine-tuned based off this model for the
Zindi News Classification Challenge#### More Details:
For more details and Demo please check HF Swahili Space