Update README.md

README.md

@@ -20,11 +20,12 @@ model-index:
     - name: F1
       type: f1
       value: 0.482
+license: apache-2.0
 ---
 
 # Text Classification GoEmotions
 
-This a ONNX quantized model and is fined-tuned version of [nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large](https://huggingface.co/nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large) on the on the [go_emotions](https://huggingface.co/datasets/go_emotions) dataset using [tasinho/text-classification-goemotions](https://huggingface.co/tasinhoque/text-classification-goemotions) as teacher model.
+This a ONNX quantized model and is fined-tuned version of [MiniLMv2-L6-H384](https://huggingface.co/nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large) on the on the [go_emotions](https://huggingface.co/datasets/go_emotions) dataset using [tasinho/text-classification-goemotions](https://huggingface.co/tasinhoque/text-classification-goemotions) as teacher model.
 The original model can be found [here](https://huggingface.co/minuva/MiniLMv2-goemotions-v2)
 
 # Optimum
@@ -164,4 +165,4 @@ The following hyperparameters were used during training:
 
 # Deployment
 
-Check [our repository](https://github.com/minuva/emotion-prediction-serverless) to see how to easily deploy this model in a serverless environment with fast CPU inference and light resource utilization.
+Check out our [fast-nlp-text-emotion repository](https://github.com/minuva/fast-nlp-text-emotion) for a FastAPI based server to easily deploy this model on CPU devices.