62 lines
		
	
	
	
		
			3.2 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
			
		
		
	
	
			62 lines
		
	
	
	
		
			3.2 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
# Bark
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In this directory, you will find examples on how you could use BigDL-LLM `optimize_model` API to accelerate Bark models. For illustration purposes, we utilize the [suno/bark](https://huggingface.co/suno/bark) as reference Bark models.
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## 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: Synthesize speech with the given input text
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In the example [synthesize_speech.py](./synthesize_speech.py), we show a basic use case for Bark model to synthesize speech based on the given text, with BigDL-LLM INT4 optimizations.
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### 1. Install
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We suggest using conda to manage the Python environment. For more information about conda installation, please refer to [here](https://docs.conda.io/en/latest/miniconda.html#).
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After installing conda, create a Python environment for BigDL-LLM:
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```bash
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conda create -n llm python=3.9 # recommend to use Python 3.9
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conda activate llm
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pip install --pre --upgrade bigdl-llm[all] # install the latest bigdl-llm nightly build with 'all' option
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pip install TTS scipy
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```
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### 2. Download Bark model
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Before running the example, you need to download Bark model to local folder:
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```python
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from huggingface_hub import snapshot_download
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model_path = snapshot_download(repo_id='suno/bark',
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                               local_dir='bark/') # you can change `local_dir` parameter to specify any local folder
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```
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Please refer to [here](https://huggingface.co/docs/huggingface_hub/guides/download#download-files-to-local-folder) for more information about `snapshot_download`.
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### 3. Run
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After setting up the Python environment and downloading Bark model, you could run the example by following steps.
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#### 3.1 Client
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On client Windows machines, it is recommended to run directly with full utilization of all cores:
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```powershell
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# make sure `--model-path` corresponds to the local folder of downloaded model
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python ./synthesize_speech.py --model-path 'bark/' --text "This is an example text for synthesize speech."
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```
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More information about arguments can be found in [Arguments Info](#33-arguments-info) section.
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#### 3.2 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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# make sure `--model-path` corresponds to the local folder of downloaded model
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numactl -C 0-47 -m 0 python ./synthesize_speech.py --model-path 'bark/' --text "This is an example text for synthesize speech."
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```
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More information about arguments can be found in [Arguments Info](#33-arguments-info) section.
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#### 3.3 Arguments Info
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In the example, several arguments can be passed to satisfy your requirements:
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- `--model-path MODEL_PATH`: **required**, argument defining the local path to the Bark model checkpoint folder.
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- `--text TEXT`: argument defining the text to synthesize speech. It is default to be `"This is an example text for synthesize speech."`.
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