Update README.md

README.md

@@ -8,6 +8,20 @@ datasets:
 
 ## Swahili News Classification with BERT
 
+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.
+
+This [model](https://huggingface.co/flax-community/bert-base-uncased-swahili) was used as the base and fine-tuned for this task.
+
+## How to use
+
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+  
+tokenizer = AutoTokenizer.from_pretrained("flax-community/bert-swahili-news-classification")
+
+model = AutoModelForSequenceClassification.from_pretrained("flax-community/bert-swahili-news-classification")
+```
+
 
 ```
 Eval metrics (10% valid set): {'accuracy': 0.9114740008594757}