Open Stark-zheng opened 6 days ago
微调量化后推理报错
推理代码: from transformers import AutoTokenizer, TextGenerationPipeline, AutoModelForCausalLM
quantized_model_dir = "xxx_int4"
model = AutoModelForCausalLM.from_pretrained( quantized_model_dir, device_map="auto", trust_remote_code=True ).eval()
image_path = 'xxx/image1.png' response, history = model.chat(tokenizer, query=f'{image_path}这是什么', history=None) print(response)
错误: OSError: /datadisk2/_1009_qlora_ds_adddataset_cleanv1_int4 does not appear to have a file named modeling_qwen.py. Checkout 'https://huggingface.co//datadisk2/_1009_qlora_ds_adddataset_cleanv1_int4/tree/None' for available files.
使用vllm部署报错:
KeyError: 'transformer.h.0.attn.c_attn.g_idx'
No response
- OS: - Python: - Transformers: - PyTorch: - CUDA (`python -c 'import torch; print(torch.version.cuda)'`):
量化完直接推理:response, history = model.chat(tokenizer, query=test_data[0], history=None)
报错:AttributeError: 'QuantLinear' object has no attribute 'q4'
是否已有关于该错误的issue或讨论? | Is there an existing issue / discussion for this?
该问题是否在FAQ中有解答? | Is there an existing answer for this in FAQ?
当前行为 | Current Behavior
微调量化后推理报错
推理代码: from transformers import AutoTokenizer, TextGenerationPipeline, AutoModelForCausalLM
quantized_model_dir = "xxx_int4"
model = AutoModelForCausalLM.from_pretrained( quantized_model_dir, device_map="auto", trust_remote_code=True ).eval()
Either a local path or an url between tags.
image_path = 'xxx/image1.png' response, history = model.chat(tokenizer, query=f'{image_path}这是什么', history=None) print(response)
错误: OSError: /datadisk2/_1009_qlora_ds_adddataset_cleanv1_int4 does not appear to have a file named modeling_qwen.py. Checkout 'https://huggingface.co//datadisk2/_1009_qlora_ds_adddataset_cleanv1_int4/tree/None' for available files.
使用vllm部署报错:
KeyError: 'transformer.h.0.attn.c_attn.g_idx'
期望行为 | Expected Behavior
No response
复现方法 | Steps To Reproduce
No response
运行环境 | Environment
备注 | Anything else?
No response