ros/LLaMA-Factory
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

update readme

Browse Source 
Former-commit-id: bc861f76706df3f643028f1dfc8ec2044b067a08
This commit is contained in:
hiyouga
2024-05-28 19:35:52 +08:00
parent 9138a7a5ba
commit ae3a88d3a7
3 changed files with 6 additions and 9 deletions
Download Patch File Download Diff File Expand all files Collapse all files

7
README.md
View File

@@ -395,9 +395,6 @@ See [examples/README.md](examples/README.md) for advanced usage (including distr
### Fine-Tuning with LLaMA Board GUI (powered by [Gradio](https://github.com/gradio-app/gradio))
> [!IMPORTANT]
> LLaMA Board GUI only supports training on a single GPU.
#### Use local environment
```bash
@@ -451,7 +448,7 @@ export USE_MODELSCOPE_HUB=1 # `set USE_MODELSCOPE_HUB=1` for Windows
Train the model by specifying a model ID of the ModelScope Hub as the `model_name_or_path`. You can find a full list of model IDs at [ModelScope Hub](https://modelscope.cn/models), e.g., `LLM-Research/Meta-Llama-3-8B-Instruct`.
### Use W&B Logging
### Use W&B Logger
To use [Weights & Biases](https://wandb.ai) for logging experimental results, you need to add the following arguments.
@@ -460,6 +457,8 @@ report_to: wandb
run_name: test_run # optional
```
Set `WANDB_API_KEY` to [your key](https://wandb.ai/authorize) when launching training tasks to log in with your W&B account.
## Projects using LLaMA Factory
If you have a project that should be incorporated, please contact via email or create a pull request.