74 lines
4.1 KiB
Markdown
74 lines
4.1 KiB
Markdown
# Whisper
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In this directory, you will find examples on how you could apply BigDL-LLM INT4 optimizations on general pytorch models, for example Openai Whisper models. For illustration purposes, we utilize the [whisper-tiny](https://github.com/openai/whisper/blob/main/model-card.md) as a reference Whisper model.
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## 0. Requirements
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To run these examples with BigDL-LLM, 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 `transcribe()` 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 `transcribe()` API, with BigDL-LLM INT4 optimizations.
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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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pip install bigdl-llm[all] # install bigdl-llm with 'all' option
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pip install -U openai-whisper
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pip install librosa # required by audio processing
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```
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### 2. 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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- `--model-name MODEL_NAME`: argument defining the model name(tiny, medium, base, etc.) for the Whisper model to be downloaded. It is one of the official model names listed by `whisper.available_models()`, or path to a model checkpoint containing the model dimensions and the model state_dict. It is default to be `'tiny'`.
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- `--audio-file AUDIO_FILE`: argument defining the path of the audio file to be recognized.
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- `--language LANGUAGE`: argument defining language to be transcribed. It is default to be `english`.
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> **Note**: When loading the model in 4-bit, BigDL-LLM converts linear layers in the model into INT4 format. In theory, a *X*B model saved in 16-bit will requires approximately 2*X* GB of memory for loading, and ~0.5*X* GB memory for further inference.
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>
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> Please select the appropriate size of the Whisper model based on the capabilities of your machine.
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#### 2.1 Client
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On client Windows machine, it is recommended to run directly with full utilization of all cores:
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```powershell
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python ./recognize.py --audio-file /PATH/TO/AUDIO_FILE
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```
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#### 2.2 Server
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For optimal performance on server, it is recommended to set several environment variables (refer to [here](../README.md#best-known-configuration-on-linux) for more information), and run the example with all the physical cores of a single socket.
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E.g. on Linux,
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```bash
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# set BigDL-Nano env variables
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source bigdl-nano-init
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# e.g. for a server with 48 cores per socket
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export OMP_NUM_THREADS=48
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numactl -C 0-47 -m 0 python ./recognize.py
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```
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#### 2.3 Sample Output
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#### [whisper-tiny](https://github.com/openai/whisper/blob/main/model-card.md)
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For audio file(.wav) download from https://www.youtube.com/watch?v=-LIIf7E-qFI, it should be extracted as:
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```log
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[00:00.000 --> 00:10.000] I don't know who you are.
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[00:10.000 --> 00:15.000] I don't know what you want.
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[00:15.000 --> 00:21.000] If you're looking for ransom, I can tell you I don't know money, but what I do have.
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[00:21.000 --> 00:24.000] I'm a very particular set of skills.
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[00:24.000 --> 00:27.000] The skills I have acquired are very long career.
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[00:27.000 --> 00:31.000] The skills that make me a nightmare for people like you.
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[00:31.000 --> 00:35.000] If you let my daughter go now, that'll be the end of it.
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[00:35.000 --> 00:39.000] I will not look for you. I will not pursue you.
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[00:39.000 --> 00:45.000] But if you don't, I will look for you. I will find you.
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[00:45.000 --> 00:48.000] And I will kill you.
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[00:48.000 --> 00:53.000] Good luck.
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Inference time: xxxx s
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-------------------- Output --------------------
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I don't know who you are. I don't know what you want. If you're looking for ransom, I can tell you I don't know money, but what I do have. I'm a very particular set of skills. The skills I have acquired are very long career. The skills that make me a nightmare for people like you. If you let my daughter go now, that'll be the end of it. I will not look for you. I will not pursue you. But if you don't, I will look for you. I will find you. And I will kill you. Good luck.
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```
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