使用model.save_pretrained('PATH') 将模型保存到指定路径。 使用MODEL_NAME.from_pretrained('PATH') 来加载模型。 二、展示效果文本分类 from transformers import pipeline, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased") model = pipeline("text-classification", model="distilbert...
tokenizer.save_pretrained(model_path,trust_remote_code=True,revision="main") model.save_pretrained(model_path,trust_remote_code=True,revision="main") ``` 然后再次调用时,用本地的`modelpath`替换HF路径即可。
from transformers import AutoModelForCausalLM, AutoTokenizer from peft import PeftModel model_name = "some_repo/some_model" save_path = "path/to/saved_model" save_path_tokenizer = "path/to/saved_tokenizer" # Could be the same as save_path # Either, load a saved resiz...
# 下载的数据集名称, model_name = 'keremberke/plane-detection' # 数据集保存的路径 save_path = 'datasets' #name参数为full或mini,full表示下载全部数据,mini表示下载部分少量数据 dataset = load_dataset(model_name, name="full") dataset.save_to_disk(save_path) 1. 2. 3. 4. 5. 6. 7. 8. ...
Model,也就是各种各样的模型。除了初始的Bert、GPT等基本模型,针对下游任务,还定义了诸如BertForQuestionAnswering等下游任务模型。模型导出时将生成config.json和pytorch_model.bin参数文件。前者就是1中的配置文件,这和我们的直觉相同,即config和model应该是紧密联系在一起的两个类。后者其实和torch.save()存储得到的...
目前，我遇到过两个与HuggingFace cache相关的问题。一个是关于datasets库的问题。在使用load_dataset函数...
hf_model_path="IDEA-CCNL/Wenzhong-GPT2-110M" tokenizer=GPT2Tokenizer.from_pretrained(hf_model_path) model=GPT2LMHeadModel.from_pretrained(hf_model_path) # 假设经过了微调 model.save_pretrained("./saved_model/") 1. 2. 3. 4. 5. ...
pretrained_model_name_or_path=model_path, low_cpu_mem_usage=True, trust_remote_code=True, torch_dtype=torch.float16) #这里指定float16格式 #safe_serialization=True会保存为safetensor格式model.save_pretrained(model_path,safe_serialization=True) ...
model_name_or_path ="bigscience/mt0-large" tokenizer_name_or_path ="bigscience/mt0-large" 创建PEFT方法对应的配置 peft_config = LoraConfig( task_type=TaskType.SEQ_2_SEQ_LM, inference_mode=False, r=8, lora_alpha=32, lora_dropout=0.1 ...
然后以较低的save_steps运行训练命令。deepspeed train_freeform.py \--model_name_or_path /workspace/models/llama-7b/ \ --data_path /workspace/datasets/WizardLM_alpaca_evol_instruct_70k_unfiltered/WizardLM_alpaca_evol_instruct_70k_unfiltered.json \--output_dir /workspace/models/WizardLM-7B-...