43 lines
2.2 KiB
Markdown
43 lines
2.2 KiB
Markdown
# Whisper
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In this directory, you will find examples on how you could apply BigDL-LLM INT4 optimizations on Whisper models on [Intel GPUs](../README.md). For illustration purposes, we utilize the [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) as a reference Whisper model.
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## 0. Requirements
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To run these examples with BigDL-LLM on Intel GPUs, we have some recommended requirements for your machine, please refer to [here](../README.md#recommended-requirements) for more information.
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## Example: Recognize Tokens using `generate()` API
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In the example [recognize.py](./recognize.py), we show a basic use case for a Whisper model to conduct transcription using `generate()` API, with BigDL-LLM INT4 optimizations on Intel GPUs.
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### 1. Install
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We suggest using conda to manage environment:
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```bash
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conda create -n llm python=3.9
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conda activate llm
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# below command will install intel_extension_for_pytorch==2.0.110+xpu as default
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# you can install specific ipex/torch version for your need
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pip install --pre --upgrade bigdl-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu
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pip install datasets soundfile librosa # required by audio processing
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```
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### 2. Configures OneAPI environment variables
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```bash
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source /opt/intel/oneapi/setvars.sh
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```
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### 3. Run
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```
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python ./recognize.py --repo-id-or-model-path REPO_ID_OR_MODEL_PATH --repo-id-or-data-path REPO_ID_OR_DATA_PATH --language LANGUAGE
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```
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Arguments info:
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- `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the Whisper model to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'openai/whisper-tiny'`.
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- `--repo-id-or-data-path REPO_ID_OR_DATA_PATH`: argument defining the huggingface repo id for the audio dataset to be downloaded, or the path to the huggingface dataset folder. It is default to be `'hf-internal-testing/librispeech_asr_dummy'`.
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- `--language LANGUAGE`: argument defining language to be transcribed. It is default to be `english`.
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#### Sample Output
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#### [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny)
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```log
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Inference time: xxxx s
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-------------------- Output --------------------
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[' Mr. Quilter is the apostle of the middle classes and we are glad to welcome his gospel.']
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```
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