update readme

README.md

@@ -1,3 +1,55 @@
 ---
 license: apache-2.0
+datasets:
+- librispeech_asr
+metrics:
+- wer
+pipeline_tag: automatic-speech-recognition
+tags:
+- automatic-speech-recognition
+- int8
+- ONNX
+- PostTrainingDynamic
+- Intel® Neural Compressor
+- neural-compressor
+library_name: transformers
 ---
+
+## Model Details: INT8 Whisper large
+
+Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. Trained on 680k hours of labelled data, Whisper models demonstrate a strong ability to generalise to many datasets and domains without the need for fine-tuning.
+
+This int8 ONNX model is generated by [neural-compressor](https://github.com/intel/neural-compressor) and the fp32 model can be exported with below command:
+```shell
+optimum-cli export onnx --model openai/whisper-large whisper-large-with-past/ --task automatic-speech-recognition-with-past --opset 13
+```
+
+| Model Detail | Description |
+| ----------- | ----------- | 
+| Model Authors - Company | Intel | 
+| Date | May 15, 2022 | 
+| Version | 1 | 
+| Type | Speech Recognition | 
+| Paper or Other Resources | - | 
+| License | Apache 2.0 |
+| Questions or Comments | [Community Tab](https://huggingface.co/Intel/whisper-large-int8-dynamic/discussions)|
+
+| Intended Use | Description |
+| ----------- | ----------- | 
+| Primary intended uses | You can use the raw model for automatic speech recognition inference | 
+| Primary intended users | Anyone doing automatic speech recognition inference | 
+| Out-of-scope uses | This model in most cases will need to be fine-tuned for your particular task.  The model should not be used to intentionally create hostile or alienating environments for people.|
+
+
+### How to use
+
+Download the model and script by cloning the repository:
+```shell
+git clone https://huggingface.co/Intel/whisper-large-int8-dynamic
+```
+
+## Metrics (Model Performance):
+| Model  | Model Size (GB) | wer |
+|---|:---:|:---:|
+| FP32 |9.4|3.04|
+| INT8 |2.4|2.80|