Update README.md

README.md

@@ -25,6 +25,7 @@ model-index:
 # Text Classification GoEmotions
 
 This model is a 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.
+The quantized version in ONNX format can be found [here](https://huggingface.co/minuva/MiniLMv2-goemotions-v2-onnx)
 
 # Load the Model
 
@@ -44,7 +45,6 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 40
 
 
 # Metrics (comparison with teacher model)
@@ -54,7 +54,7 @@ The following hyperparameters were used during training:
 | tasinhoque/text-classification-goemotions (355M) |      MiniLMv2-L6-H384-goemotions-v2    | Validation  | 0.514252 |0.484898 |
 | tasinhoque/text-classification-goemotions (33M) |      MiniLMv2-L6-H384-goemotions-v2    | Test  | 0.501937 |  0.486890 |
 
-# Training Code, Evaluation & Deployment
+# Deployment
 
-Check 
+Check [our repository](https://github.com/minuva/emotion-prediction-serverless) to see how to easily deploy this (quantized) model in a serverless environment with fast CPU inference and light resource utilization.