Releases
v0.8.0
v0.8.0: GLM-4, Qwen2, PaliGemma, KTO, SimPO
Support single-node distributed training in Web UI
Add dropdown menu for easily resuming from checkpoints and picking saved configurations by @hiyouga and @hzhaoy in #4053
Support selecting checkpoints of full/freeze tuning
Add throughput metrics to LlamaBoard by @injet-zhou in #4066
Faster UI loading
New features
Add KTO algorithm by @enji-zhou in #3785
Add SimPO algorithm by @hiyouga
Support passing max_lora_rank
to the vLLM backend by @jue-jue-zi in #3794
Support preference datasets in sharegpt format and remove big files from git repo by @hiyouga in #3799
Support setting system messages in CLI inference by @ycjcl868 in #3812
Add num_samples
option in dataset_info.json
by @seanzhang-zhichen in #3829
Add NPU docker image by @dongdongqiang2018 in #3876
Improve NPU document by @MengqingCao in #3930
Support SFT packing with greedy knapsack algorithm by @AlongWY in #4009
Add llamafactory-cli env
for bug report
Support image input in the API mode
Support random initialization via the train_from_scratch
argument
Initialize CI
New models
Base models
Qwen2 (0.5B/1.5B/7B/72B/MoE) 📄
PaliGemma-3B (pt/mix) 📄🖼️
GLM-4-9B 📄
Falcon-11B 📄
DeepSeek-V2-Lite (16B) 📄
Instruct/Chat models
Qwen2-Instruct (0.5B/1.5B/7B/72B/MoE) 📄🤖
Mistral-7B-Instruct-v0.3 📄🤖
Phi-3-small-8k-instruct (7B) 📄🤖
Aya-23 (8B/35B) 📄🤖
OpenChat-3.6-8B 📄🤖
GLM-4-9B-Chat 📄🤖
TeleChat-12B-Chat by @hzhaoy in #3958 📄🤖
Phi-3-medium-8k-instruct (14B) 📄🤖
DeepSeek-V2-Lite-Chat (16B) 📄🤖
Codestral-22B-v0.1 📄🤖
New datasets
Pre-training datasets
FineWeb (en)
FineWeb-Edu (en)
Supervised fine-tuning datasets
Ruozhiba-GPT4 (zh)
STEM-Instruction (zh)
Preference datasets
Argilla-KTO-mix-15K (en)
UltraFeedback (en)
Bug fix
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