--> 461 config, kwargs = AutoConfig.from_pretrained( 462 pretrained_model_name_or_path, 463 return_unused_kwargs=True, 464 trust_remote_code=trust_remote_code, 465 **hub_kwargs, 466 **kwargs, 467 ) 469 # if torch_dtype=auto was passed here, ensure to pass it on ...
使用以下代码从该配置文件恢复该模型： from transformers import AutoConfig, AutoTokenizer, AutoModelFor...
1613 + model_config = AutoConfig.from_pretrained( 1614 + model_dir, trust_remote_code=True) 1615 + model_config._flash_attn_2_enabled = kwargs.pop('use_flash_attn', False) 1616 + return get_model_tokenizer_from_repo( 1617 + model_dir, 1618 + torch_dtype, 1619 + model_kw...
以下是一个使用PyTorch框架和HuggingFace库进行单步微调的示例代码：from transformers import AutoTokenizer, ...
你需要将self_cognition_sample=500注释掉， 或者将model_name, model_author的注释取消掉--此回答整理...
from_pretrained(self.vision_tower_name) self.vision_tower.requires_grad_(False) self.is_loaded = True CLIPVisionTower = get_class_from_dynamic_module('build_mlp.CLIPVisionTower', model_dir) CLIPVisionTower.load_model = load_model model_config = AutoConfig.from_pretrained(model_dir, trust_...
modelscope是哪里出了问题呢？有重复，返回的json数据不能解析。参考以下链接https://modelscope.cn/...
2460 + model_config = AutoConfig.from_pretrained( 2461 + model_dir, trust_remote_code=True) 2462 + use_flash_attn = kwargs.pop('use_flash_attn', False) 2463 + model_config.flash_attn = use_flash_attn 2464 + return get_model_tokenizer_from_repo( 2465 + model_dir, 2466 + torch_dt...
65 + new_config = AutoConfig.from_pretrained("/path/to/new_config_dir") # 新config 的文件夹路径 66 + 67 + # 1. 替换 ViT 到 LLM 的 merger(aligner) 层 68 + new_merger = Qwen2_5_VLPatchMerger( 69 + dim=new_visual_config.out_hidden_size, 70 + context_dim=new_visual_config....