支持模型

最近更新时间: 2026-06-30 15:06:00

TACO-LLM 支持 Huggingface 模型格式的多种生成式 Transformer 模型。下面列出了 TACO-LLM 目前支持的模型架构和对应的常用模型。

Decoder-only 语言模型

Architecture Models Example HuggingFace Models LoRA
BaiChuanForCausalLM Baichuan & Baichuan2 baichuan-inc/Baichuan2-13B-Chat, baichuan-inc/Baichuan-7B, etc. Supported
BloomForCausalLM BLOOM, BLOOMZ, BLOOMChat bigscience/bloom, bigscience/bloomz, etc. -
ChatGLMModel ChatGLM THUDM/chatglm2-6b, THUDM/chatglm3-6b, etc. Supported
FalconForCausalLM Falcon tiiuae/falcon-7b, tiiuae/falcon-40b, tiiuae/falcon-rw-7b, etc. -
GemmaForCausalLM Gemma google/gemma-2b, google/gemma-7b, etc. Supported
Gemma2ForCausalLM Gemma2 google/gemma-2-9b, google/gemma-2-27b, etc. Supported
GPT2LMHeadModel GPT-2 gpt2, gpt2-xl, etc. -
GPTBigCodeForCausalLM StarCoder, SantaCoder, WizardCoder bigcode/starcoder, bigcode/gpt_bigcode-santacoder, WizardLM/WizardCoder-15B-V1.0, etc. Supported
GPTJForCausalLM GPT-J EleutherAI/gpt-j-6b, nomic-ai/gpt4all-j, etc. -
GPTNeoXForCausalLM GPT-NeoX, Pythia, OpenAssistant, Dolly V2, StableLM EleutherAI/gpt-neox-20b, EleutherAI/pythia-12b, OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5, databricks/dolly-v2-12b, stabilityai/stablelm-tuned-alpha-7b, etc. -
InternLMForCausalLM InternLM internlm/internlm-7b, internlm/internlm-chat-7b, etc. Supported
InternLM2ForCausalLM InternLM2 internlm/internlm2-7b, internlm/internlm2-chat-7b, etc. -
LlamaForCausalLM Llama 3.1, Llama 3, Llama 2, LLaMA, Yi meta-llama/Meta-Llama-3.1-405B-Instruct, meta-llama/Meta-Llama-3.1-70B, meta-llama/Meta-Llama-3-70B-Instruct, meta-llama/Llama-2-70b-hf, 01-ai/Yi-34B, etc. Supported
MistralForCausalLM Mistral, Mistral-Instruct mistralai/Mistral-7B-v0.1, mistralai/Mistral-7B-Instruct-v0.1, etc. Supported
MixtralForCausalLM Mixtral-8x7B, Mixtral-8x7B-Instruct mistralai/Mixtral-8x7B-v0.1, mistralai/Mixtral-8x7B-Instruct-v0.1, mistral-community/Mixtral-8x22B-v0.1, etc. Supported
NemotronForCausalLM Nemotron-3, Nemotron-4, Minitron nvidia/Minitron-8B-Base, mgoin/Nemotron-4-340B-Base-hf-FP8, etc. Supported
OPTForCausalLM OPT, OPT-IML facebook/opt-66b,
facebook/opt-iml-max-30b, etc.
PhiForCausalLM Phi microsoft/phi-1_5, microsoft/phi-2, etc. Supported
Phi3ForCausalLM Phi-3 microsoft/Phi-3-mini-4k-instruct,
microsoft/Phi-3-mini-128k-instruct,
microsoft/Phi-3-medium-128k-instruct, etc.
-
Phi3SmallForCausalLM Phi-3-Small microsoft/Phi-3-small-8k-instruct, microsoft/Phi-3-small-128k-instruct, etc. -
PhiMoEForCausalLM Phi-3.5-MoE microsoft/Phi-3.5-MoE-instruct
, etc.
-
QWenLMHeadModel Qwen Qwen/Qwen-7B, Qwen/Qwen-7B-Chat, etc. -

Qwen2ForCausalLM
Qwen2 Qwen/Qwen2-beta-7B, Qwen/Qwen2-beta-7B-Chat, etc. Supported
Qwen2MoeForCausalLM Qwen2MoE Qwen/Qwen1.5-MoE-A2.7B, Qwen/Qwen1.5-MoE-A2.7B-Chat, etc. -
StableLmForCausalLM StableLM stabilityai/stablelm-3b-4e1t/ , stabilityai/stablelm-base-alpha-7b-v2, etc. -
Starcoder2ForCausalLM Starcoder2 bigcode/starcoder2-3b, bigcode/starcoder2-7b, bigcode/starcoder2-15b, etc. -
XverseForCausalLM Xverse xverse/XVERSE-7B-Chat, xverse/XVERSE-13B-Chat, xverse/XVERSE-65B-Chat, etc. -

多模态语言模型

ArchitectureModelsModalitiesExample HuggingFace ModelsLoRA
InternVLChatModelInternVL2Image(E+)OpenGVLab/InternVL2-4B, OpenGVLab/InternVL2-8B, etc.-
LlavaForConditionalGenerationLLaVA-1.5Image(E+)llava-hf/llava-1.5-7b-hf, llava-hf/llava-1.5-13b-hf, etc.-
LlavaNextForConditionalGenerationLLaVA-NeXTImage(E+)llava-hf/llava-v1.6-mistral-7b-hf, llava-hf/llava-v1.6-vicuna-7b-hf, etc.-
LlavaNextVideoForConditionalGenerationLLaVA-NeXT-VideoVideollava-hf/LLaVA-NeXT-Video-7B-hf, etc. (see note)-
PaliGemmaForConditionalGenerationPaliGemmaImage(E)google/paligemma-3b-pt-224, google/paligemma-3b-mix-224, etc.-
Phi3VForCausalLMPhi-3-Vision, Phi-3.5-VisionImage(E+)microsoft/Phi-3-vision-128k-instruct, microsoft/Phi-3.5-vision-instruct etc.-
PixtralForConditionalGenerationPixtralImage(+)mistralai/Pixtral-12B-2409-
QWenLMHeadModelQwen-VLImage(E+)Qwen/Qwen-VL, Qwen/Qwen-VL-Chat, etc.-
Qwen2VLForConditionalGenerationQwen2-VL (see note)Image(+) / Video(+)Qwen/Qwen2-VL-2B-Instruct, Qwen/Qwen2-VL-7B-Instruct, Qwen/Qwen2-VL-72B-Instruct, etc.-

说明:

  • E: 表示 Pre-computed embeddings 可以作为多模态输入。
  • +: 表示一个 prompt 可以插入多个多模态输入。