v0.7.1: Ascend NPU Support, Yi-VL Models

🚨🚨 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, use llamafactory-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