when I use local lora model, I got this
Traceback (most recent call last): File "/datalc2/LLM/Video_caption/V2/multi_token/scripts/serve_model.py", line 31, in <module> model, tokenizer = load_trained_lora_model( File "/datalc2/LLM/Video_caption/V2/multi_token/multi_token/inference.py", line 74, in load_trained_lora_model model = PeftModel.from_pretrained(model, model_lora_path) File "/root/miniconda3/envs/video_caption/lib/python3.10/site-packages/peft/peft_model.py", line 356, in from_pretrained model.load_adapter(model_id, adapter_name, is_trainable=is_trainable, **kwargs) File "/root/miniconda3/envs/video_caption/lib/python3.10/site-packages/peft/peft_model.py", line 727, in load_adapter adapters_weights = load_peft_weights(model_id, device=torch_device, **hf_hub_download_kwargs) File "/root/miniconda3/envs/video_caption/lib/python3.10/site-packages/peft/utils/save_and_load.py", line 297, in load_peft_weights has_remote_safetensors_file = file_exists( File "/root/miniconda3/envs/video_caption/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 110, in _inner_fn validate_repo_id(arg_value) File "/root/miniconda3/envs/video_caption/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 158, in validate_repo_id raise HFValidationError( huggingface_hub.utils._validators.HFValidationError: Repo id must be in the form 'repo_name' or 'namespace/repo_name': '/datalc2/Downloadmodel/Mistral-7B-LoRA-Multi-VisionCLIPPool-LLAVA/'. Userepo_typeargument if needed.
when I use local lora model, I got this
Traceback (most recent call last): File "/datalc2/LLM/Video_caption/V2/multi_token/scripts/serve_model.py", line 31, in <module> model, tokenizer = load_trained_lora_model( File "/datalc2/LLM/Video_caption/V2/multi_token/multi_token/inference.py", line 74, in load_trained_lora_model model = PeftModel.from_pretrained(model, model_lora_path) File "/root/miniconda3/envs/video_caption/lib/python3.10/site-packages/peft/peft_model.py", line 356, in from_pretrained model.load_adapter(model_id, adapter_name, is_trainable=is_trainable, **kwargs) File "/root/miniconda3/envs/video_caption/lib/python3.10/site-packages/peft/peft_model.py", line 727, in load_adapter adapters_weights = load_peft_weights(model_id, device=torch_device, **hf_hub_download_kwargs) File "/root/miniconda3/envs/video_caption/lib/python3.10/site-packages/peft/utils/save_and_load.py", line 297, in load_peft_weights has_remote_safetensors_file = file_exists( File "/root/miniconda3/envs/video_caption/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 110, in _inner_fn validate_repo_id(arg_value) File "/root/miniconda3/envs/video_caption/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 158, in validate_repo_id raise HFValidationError( huggingface_hub.utils._validators.HFValidationError: Repo id must be in the form 'repo_name' or 'namespace/repo_name': '/datalc2/Downloadmodel/Mistral-7B-LoRA-Multi-VisionCLIPPool-LLAVA/'. Userepo_typeargument if needed.