Update README.md

README.md

@@ -1,3 +1,49 @@
 ---
+language: en
 license: mit
+datasets:
+- glue
+- mrpc
+metrics:
+- f1
+tags:
+- text-classfication
+- nlp
+- neural-compressor
+- PostTrainingsDynamic
+- int8
+- Intel® Neural Compressor
+- albert
 ---
+
+# Dynamically quantized Albert base finetuned MPRC
+
+## Table of Contents
+- [Model Details](#model-details)
+- [How to Get Started With the Model](#how-to-get-started-with-the-model)
+
+## Model Details
+**Model Description:** This model is a [Albert](https://huggingface.co/textattack/albert-base-v2-MRPC) fine-tuned on MPRC dynamically quantized with [optimum-intel](https://github.com/huggingface/optimum-intel) through the usage of [huggingface/optimum-intel](https://github.com/huggingface/optimum-intel) through the usage of [Intel® Neural Compressor](https://github.com/intel/neural-compressor). 
+- **Model Type:** Text Classification
+- **Language(s):** English
+- **License:** Apache-2.0
+- **Parent Model:** For more details on the original model, we encourage users to check out [this](https://huggingface.co/textattack/albert-base-v2-MRPC) model card.
+
+## How to Get Started With the Model
+
+### PyTorch
+
+To load the quantized model, you can do as follows:
+
+```python
+from optimum.intel.neural_compressor.quantization import IncQuantizedModelForSequenceClassification
+
+model = IncQuantizedModelForSequenceClassification.from_pretrained("Intel/albert-base-v2-MRPC-int8")
+```
+
+#### Test result
+
+|   |INT8|FP32|
+|---|:---:|:---:|
+| **Accuracy (eval-f1)** |0.9193|0.9263|
+| **Model size (MB)**  |45.0|46.7|