importdatasetsfromdatasetsimportDownloadMode# resume_download是断点续传,max_retries可以在短暂断连后等待一个足够长到恢复连接的间隔config=datasets.DownloadConfig(resume_download=True,max_retries=100)data=datasets.load_dataset('natural_questions',cache_dir=r'',download_config=config,download_mode=DownloadMode...
super(CustomModel,self).__init__() self.num_labels = num_labels #Load Model with given checkpoint and extract its body self.model = model = AutoModel.from_pretrained(checkpoint,config=AutoConfig.from_pretrained(checkpoint, output_attentions=True,output_hidden_states=True)) self.dropout = nn.D...
To work with the AutoTokenizer you also need to save the config to load it offline: from transformers import AutoTokenizer, AutoConfig tokenizer = AutoTokenizer.from_pretrained('xlm-roberta-base') config = AutoConfig.from_pretrained('xlm-roberta-base') tokenizer.save_pretrained('YOURPATH') confi...
model = AutoModelForCausalLM.from_pretrained(model_name_or_path, torch_dtype=torch.float16, cache_dir=cache_path) I got the error FileNotFoundError: [Errno 2] No such file or directory: '../../blobs/2122720188751bb5b1d1a28480cbca2d216c63f2' -> '/home/hanyuan/.cache/huggingface/hub/...
fromtransformers import AutoModelForCausalLMfromdatasets import load_datasetfromtrl import SFTTrainer dataset = load_dataset("imdb",split="train") model = AutoModelForCausalLM.from_pretrained("facebook/opt-350m") peft_config = LoraConfig(r=16,lora_alpha=32,lora_dropout=0.05,bias="none",task_...
model_id = "philschmid/flan-t5-xxl-sharded-fp16" # load model from the hub model = AutoModelForSeq2SeqLM.from_pretrained(model_id, load_in_8bit=True, device_map="auto") 现在,我们可以使用 peft 为LoRA int-8 训练作准备了。 from peft import LoraConfig, get_peft_model, prepare_model_...
from transformersimportAutoTokenizer,pipeline from trlimportAutoModelForCausalLMWithValueHead,PPOConfig,PPOTrainer from tqdmimporttqdm dataset=load_dataset("HuggingFaceH4/cherry_picked_prompts",split="train")dataset=dataset.rename_column("prompt","query")dataset=dataset.remove_columns(["meta","completion"...
# Check out https://hf.co/sd-dreambooth-library for loads of models from the community model_id ="sd-dreambooth-library/mr-potato-head" # Load the pipeline pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to ( ...
如果您没有并且模型卡没有任何文档,您将需要做出很多假设config.json 经过一番猜测,可能是这样的: fromu2netimportU2NET model = U2NET() model.load_state_dict(torch.load('full_weights.pth', map_location=torch.device('cpu'))) Run Code Online (Sandbox Code Playgroud) ...
2.1 Load the model # 确定模型导入精度ifscript_args.load_in_8bitandscript_args.load_in_4bit:...