🚨🚨 Core refactor 🚨🚨
- Add CLIs usage, now we recommend using
llamafactory-cli
to launch training and inference, the entry point is located at the cli.py - Rename files:
train_bash.py
->train.py
,train_web.py
->webui.py
,api_demo.py
->api.py
- Remove files:
cli_demo.py
,evaluate.py
,export_model.py
,web_demo.py
, usellamafactory-cli chat/eval/export/webchat
instead - Use YAML configs in examples instead of shell scripts for a pretty view
- Remove the sha1 hash check when loading datasets
- Rename arguments:
num_layer_trainable
->freeze_trainable_layers
,name_module_trainable
->freeze_trainable_modules
The above changes are made by @hiyouga in #3596
REMINDER: Now installation is mandatory to use LLaMA Factory
New features
- Support training and inference on the Ascend NPU 910 devices by @zhou-wjjw and @statelesshz (docker images are also provided)
- Support
stop
parameter in vLLM engine by @zhaonx in #3527 - Support fine-tuning token embeddings in freeze tuning via the
freeze_extra_modules
argument - Add Llama3 quickstart to readme
New models
- Base models
- Yi-1.5 (6B/9B/34B) 📄
- DeepSeek-V2 (236B) 📄
- Instruct/Chat models
- Yi-1.5-Chat (6B/9B/34B) 📄🤖
- Yi-VL-Chat (6B/34B) by @BUAADreamer in #3748 📄🖼️🤖
- Llama3-Chinese-Chat (8B/70B) 📄🤖
- DeepSeek-V2-Chat (236B) 📄🤖
Bug fix
- Add badam arguments to LlamaBoard by @codemayq in #3487
- Add openai data format to readme by @khazic in #3490
- Fix slow operation in dpo/orpo trainer by @hiyouga
- Fix badam examples by @pha123661 in #3578
- Fix download link of the nectar_rm dataset by @ZeyuTeng96 in #3588
- Add project by @Katehuuh in #3601
- Fix dockerfile by @gaussian8 in #3604
- Fix full tuning of MLLMs by @BUAADreamer in #3651
- Fix gradio environment variables by @cocktailpeanut in #3654
- Fix typo and add log in API by @Tendo33 in #3655
- Fix download link of the phi-3 model by @YUUUCC in #3683
- Fix #3559 #3560 #3602 #3603 #3606 #3625 #3650 #3658 #3674 #3694 #3702 #3724 #3728