from huggingface_hub import snapshot_download snapshot_download(repo_id="internlm/internlm2-chat-7b") 同样也可以指定 cache_dir 参数,另外还有一个 local_dir 参数,作用类似于上面的 save_pretrained。 也可以使用 huggingface_hub 提供的命令行工具 huggingface-cli download internlm/internlm2-chat-7b 如果...
python -m transformers.onnx --model=local-pt-checkpoint onnx/ TensorFlow: from transformers import AutoTokenizer, TFAutoModelForSequenceClassification# 从hub加载tokenizer和TensorFlow weightstokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased")tf_model = TFAutoModelForSequenceClassification.fro...
可以通过设置TRANSFORMERS_CACHE环境变量控制模型的保存路径,详情见 HelloWorld:huggingface 模型下载与离线加...
另外,值得注意的是from_pretrained(cache_dir)中cache_dir是存放自动下载的model/tokenizer文件与缓存的路径。 如果我们需要对训练集进行预处理: tokenized_dataset = tokenizer( raw_datasets["train"]["sentence1"], raw_datasets["train"]["sentence2"], padding=True, truncation=True,return_tensors="pt" ) ...
方法2:import transformers as ppb model = ppb.BertForSequenceClassification.from_pretrained('bert-...
# Load pretrained model and tokenizer # The .from_pretrained methods guarantee that only one local process can concurrently download model & vocab. config_kwargs = { "cache_dir": model_args.cache_dir, "revision": model_args.model_revision, ...
I'm trying to run language model finetuning script (run_language_modeling.py) from huggingface examples with my own tokenizer(just added in several tokens, see the comments). I have problem loading the tokenizer. I think the problem is with AutoTokenizer.from_pretrained('local/path/to/director...
tokenizer = GPT2Tokenizer.from_pretrained(model_path) # 加载模型 model = GPT2LMHeadModel.from_pretrained(model_path) # 定义输入文本 input_text = "Once upon a time, in a land far, far away, there was a kingdom full of" # 编码输入文本 ...
然而如果你用的huggingface-cli download gpt2 --local-dir /data/gpt2下载,即使你把模型存储到了自己指定的目录,但是你仍然可以简单的用模型的名字来引用他。即: AutoModelForCausalLM.from_pretrained("gpt2") 原理是因为huggingface工具链会在.cache/huggingface/下维护一份模型的符号链接,无论你是否指定了模型的...
File "/usr/local/lib/python3.9/dist-packages/transformers/models/auto/configuration_auto.py", line 896, in from_pretrained config_dict, unused_kwargs = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs) File "/usr/local/lib/python3.9/dist-packages/transformers/configuratio...