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# Start Agent | |
## Requirements | |
- GPU memory: At least 8GB(under quanization), 16GB or more is recommanded. | |
- Disk usage: 10GB | |
## Download Model | |
You can get the model by: | |
```bash | |
huggingface-cli download fishaudio/fish-agent-v0.1-3b --local-dir checkpoints/fish-agent-v0.1-3b | |
``` | |
Put them in the 'checkpoints' folder. | |
You also need the fish-speech model which you can download instructed by [inference](inference.md). | |
So there will be 2 folder in the checkpoints. | |
The `checkpoints/fish-speech-1.4` and `checkpoints/fish-agent-v0.1-3b` | |
## Environment Prepare | |
If you already have Fish-speech, you can directly use by adding the follow instruction: | |
```bash | |
pip install cachetools | |
``` | |
!!! note | |
Please use the Python version below 3.12 for compile. | |
If you don't have, please use the below commands to build yout environment: | |
```bash | |
sudo apt-get install portaudio19-dev | |
pip install -e .[stable] | |
``` | |
## Launch The Agent Demo. | |
To build fish-agent, please use the command below under the main folder: | |
```bash | |
python -m tools.api --llama-checkpoint-path checkpoints/fish-agent-v0.1-3b/ --mode agent --compile | |
``` | |
The `--compile` args only support Python < 3.12 , which will greatly speed up the token generation. | |
It won't compile at once (remember). | |
Then open another terminal and use the command: | |
```bash | |
python -m tools.e2e_webui | |
``` | |
This will create a Gradio WebUI on the device. | |
When you first use the model, it will come to compile (if the `--compile` is True) for a short time, so please wait with patience. | |
## Gradio Webui | |
<p align="center"> | |
<img src="../assets/figs/agent_gradio.png" width="75%"> | |
</p> | |
Have a good time! | |
## Performance | |
Under our test, a 4060 laptop just barely runs, but is very stretched, which is only about 8 tokens/s. The 4090 is around 95 tokens/s under compile, which is what we recommend. | |
# About Agent | |
The demo is an early alpha test version, the inference speed needs to be optimised, and there are a lot of bugs waiting to be fixed. If you've found a bug or want to fix it, we'd be very happy to receive an issue or a pull request. | |