tokenizer= AutoTokenizer.from_pretrained(model_path, use_fast=False)ifmodel_path.endswith("4bit"): model=AutoModelForCausalLM.from_pretrained( model_path, load_in_4bit=True, torch_dtype=torch.float16, device_map='auto')elifmodel_path.endswith("8bit"): model=AutoModelForCausalLM.from_pret...
my goal is to download the model weights from hugging face and save them locally on my server, so that I can work with the LLM on my ubuntu server where I have a gpu. does the error message below mean that the gpu ran out of room while it was trying to download the model from hu...
I am facing the following issue when I try to load xlm-roberta-base model from a given path: >> tokenizer = AutoTokenizer.from_pretrained(model_path) >> Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/user/anaconda3/lib/python3.7/site-packages/t...
per_device_train_batch_size=16, per_device_eval_batch_size=16, num_train_epochs=2, weight_decay=0.01, evaluation_strategy="epoch", save_strategy="epoch", load_best_model_at_end=True, push_to_hub=True,)trainer = Trainer( model=model, args=training_...
官网建议大家注册一个账号,方便使用Hugging Face的Model Hub。 pipeline背后的男人 Transformer中使用Pytorch和Tensorflow来训练是有微小差别的,大家在使用过程中需要注意这些区别。 从如下的例子开始,我们探究下pipeline后做了那些工作。(据说很复杂) from transformers import pipeline classifier = pipeline("sentiment...
在huggingface的github页面上,搜索自己想下载的模型。model card部分有相关加载使用介绍。files部分直接点击...
一、Load dataset 1.1 Hugging Face Hub 1.2 本地和远程文件 1.2.1 CSV 1.2.2 JSON 1.2.3 text 1.2.4 Parquet 1.2.5 内存数据(python字典和DataFrame) 1.2.6 Offline离线(见原文) 1.3 切片拆分(Slice splits) 1.3.1 字符串拆分(包括交叉验证) 1.4 Troubleshooting故障排除 1.4.1手动下载 1.4.2 Specify fe...
数据准备就绪后,可以使用它来微调 Hugging Face 模型。 笔记本:从 Hugging Face 下载数据集 此示例笔记本提供了使用 Hugging Faceload_dataset函数在 Azure Databricks 中为不同大小的数据下载和准备数据集的建议最佳做法。 从Hugging Face 最佳做法笔记本下载数据集 ...
{"torch_dtype": torch.float16}) service_context = ServiceContext.from_defaults(chunk_size=1024, llm=llm, embed_model="local") documents = SimpleDirectoryReader(docs_path).load_data() index = VectorStoreIndex.from_documents(documents, service_context=service_context)defchatbot(input_text):query_...
transformers目前已被广泛地应用到各个领域中,hugging face的transformers是一个非常常用的包,在使用预训练的模型时背后是怎么运行的,我们意义来看。 以transformers=4.5.0为例 基本使用: fromtransformersimportBertModel model = BertModel.from_pretrained('base-base-chinese') ...