Update README.md

README.md

@@ -11,7 +11,36 @@ This model identifies common events and patterns within the conversation flow. S
 
 This model should be used *only* for agent dialogs.
 
-# Usage
+
+# Optimum
+
+## Installation
+
+Install from source: 
+```bash
+python -m pip install optimum[onnxruntime]@git+https://github.com/huggingface/optimum.git
+```
+
+
+## Run the Model
+```py
+from optimum.onnxruntime import ORTModelForSequenceClassification
+from transformers import AutoTokenizer, pipeline
+
+model = ORTModelForSequenceClassification.from_pretrained('minuva/MiniLMv2-agentflow-v2-onnx', provider="CPUExecutionProvider")
+tokenizer = AutoTokenizer.from_pretrained('minuva/MiniLMv2-agentflow-v2-onnx', use_fast=True, model_max_length=256, truncation=True, padding='max_length')
+
+pipe = pipeline(task='text-classification', model=model, tokenizer=tokenizer, )
+texts = ["My apologies", "Im not sure what you mean"]
+pipe(texts)
+# [{'label': 'agent_apology_error_mistake', 'score': 0.9967106580734253},
+# {'label': 'agent_didnt_understand', 'score': 0.9975798726081848}]
+```
+
+# ONNX Runtime only
+
+A lighter solution for deployment
+
 
 ## Installation
 ```bash
@@ -20,7 +49,6 @@ pip install onnxruntime
 git clone https://huggingface.co/minuva/MiniLMv2-agentflow-v2-onnx
 ```
 
-
 ## Run the Model
 
 ```py
@@ -99,7 +127,8 @@ for result in results:
     res.append(max_score)
 
 res
-# [('agent_apology_error_mistake', 0.9991708993911743)]
+# [('agent_apology_error_mistake', 0.9991968274116516),
+# ('agent_didnt_understand', 0.9993669390678406)]
 ```
 
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