问from_config与from_pretrained在HuggingFace中的差异EN老肥近期参加Kaggle平台的比赛，因为比赛类型为Code ...
Also, are they doing the same for a model? (The function names make me think from_config only defines structures but from_pretrained also loads parameter weights.) I've seen some scripts using from_config and others using from_pretrained. I get that from_config needs a config object and f...
including 1 entities, in source file simulate.v Info: Found entity 1: modelsim_test Error: T...
AutoModel from_pretrained()是Hugging Face Transformers库中的一个功能,它可以根据给定的模型名称自动下载和加载相应的预训练模型。以下是AutoModel from_pretrained()函数的参数: model_name:模型名称,可以是预训练模型的名称或自定义模型的名称。 cache_dir:缓存目录,用于存储下载的模型文件。如果未指定,将使用默认的...
The two different methods for instantiating a model produce different losses. `from pytorch_transformers import BertForMaskedLM, BertConfig, BertTokenizer import torch tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') input_...
from transformers import AutoModelForCausalLM, AutoTokenizer from transformers.generation import GenerationConfig # 加载预训练的模型和分词器 tokenizer = AutoTokenizer.from_pretrained("gpt2") model = AutoModelForCausalLM.from_pretrained("gpt2") # 创建 GenerationConfig 对象 generation_config = Generation...
Failed to find T:\SD\ComfyUI-aki-v1\custom_nodes\comfyui_controlnet_aux\ckpts\hr16/ControlNet-HandRefiner-pruned\hrnetv2_w64_imagenet_pretrained.pth.Downloading from huggingface.cocacher folder is C:\Users\Administrator\AppData\Local\Temp, you can change it by custom_tmp_path in config....
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True) BitsAndBytesConfig,前面已经说了我们使用bitsandbytes进行量化。transformer库最近添加了对bitsandbytes的全面支持,因此使用BitsandBytesConfig可以配置bitsandbytes提供的任何量化方法,例如LLM.int8、FP4和NF4。将量化配置传递给AutoModelFor...
The PretrainedConfig class has a method for loading configs from_pretrained(). As the documentation states, the input can be either a string or a path to a config file: pretrained_model_name_or_path (:obj:`str` or :obj:`os.PathLike`): Th...
logger.info("Constructing GPT-2 model from provided config.") # Manually construct a model from scratch logger.info("Constructing model from provided config.") if isinstance(config, str): config = AutoConfig.from_pretrained(config) self.model = AutoModelForCausalLM(config=config, local_files_on...