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

support Baichuan-13B

Browse Source 
Former-commit-id: f3edfe7d42d5513fb4177be61ec4f88f1edffb1e
This commit is contained in:
hiyouga
2023-07-11 16:16:14 +08:00
parent 61988225a8
commit 1aa0997391
2 changed files with 9 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
README.md
View File

@@ -9,6 +9,8 @@
## Changelog
[23/07/11] Now we support training the **Baichuan-13B** model in this repo. Try `--model_name_or_path baichuan-inc/Baichuan-13B-Base` and `--lora_target W_pack` arguments to use the Baichuan-13B model.
[23/07/09] Now we release [FastEdit](https://github.com/hiyouga/FastEdit)⚡🩹, an easy-to-use package for editing the factual knowledge of large language models efficiently. Please follow [FastEdit](https://github.com/hiyouga/FastEdit) if you are interested.
[23/07/07] Now we support training the **InternLM-7B** model in this repo. Try `--model_name_or_path internlm/internlm-7b` argument to use the InternLM model. Remember to use `--prompt_template intern` argument when you are using the InternLM-chat model.
@@ -19,7 +21,7 @@
[23/06/22] Now we align the [demo API](src/api_demo.py) with the [OpenAI's](https://platform.openai.com/docs/api-reference/chat) format where you can insert the fine-tuned model in **arbitrary ChatGPT-based applications**.
[23/06/15] Now we support training the **baichuan-7B** model in this repo. Try `--model_name_or_path baichuan-inc/baichuan-7B` and `--lora_target W_pack` arguments to use the baichuan-7B model. If you want to train with RTX3090, use `git checkout baichuan-7b-rtx3090` to switch to the `baichuan-7b-rtx3090` branch and try the `--baichuan_rtx_gpu true` argument. (Other RTX series GPUs can also be tried)
[23/06/15] Now we support training the **Baichuan-7B** model in this repo. Try `--model_name_or_path baichuan-inc/Baichuan-7B` and `--lora_target W_pack` arguments to use the Baichuan-7B model. If you want to train with RTX3090, use `git checkout baichuan-7b-rtx3090` to switch to the `baichuan-7b-rtx3090` branch and try the `--baichuan_rtx_gpu true` argument. (Other RTX series GPUs can also be tried)
[23/06/03] Now we support quantized training and inference (aka **[QLoRA](https://github.com/artidoro/qlora)**). Try `--quantization_bit 4/8` argument to work with quantized model. (experimental feature)
@@ -30,7 +32,7 @@
- [LLaMA](https://github.com/facebookresearch/llama) (7B/13B/33B/65B)
- [BLOOM](https://huggingface.co/bigscience/bloom) & [BLOOMZ](https://huggingface.co/bigscience/bloomz) (560M/1.1B/1.7B/3B/7.1B/176B)
- [Falcon](https://huggingface.co/tiiuae/falcon-7b) (7B/40B)
- [baichuan](https://huggingface.co/baichuan-inc/baichuan-7B) (7B)
- [Baichuan](https://huggingface.co/baichuan-inc/baichuan-7B) (7B/13B)
- [InternLM](https://github.com/InternLM/InternLM) (7B)
## Supported Training Approaches