也可以使用--local-dir指定下载路径。 然后调用模型就是按照官网教的方式: # 使用Auto方法 from transformers import AutoModel, AutoTokenizer model = AutoModel.from_pretrained("hfl/rbt3") tokenizer = AutoTokenizer.from_pretrained("hfl/rbt3") # 使用pipeline方法 from transformers import pipeline pipe = ...
方法2：import transformers as ppb model = ppb.BertForSequenceClassification.from_pretrained('bert-bas...
I want to directly load a stablediffusion base safetensors model locally , but I found that it seems to only support the repository format. Is there any way to make it load the local model? Reproduction pipeline = DiffusionPipeline.from_pretrained("/onedif/models/sd/chilloutmix_NiPrunedFp32...
seems that the HuggingFacePipeline.from_model_id() method is raising an error because the model I...
A wrapped-upped pipeline has been proposed: https://github.com/hiyouga/LLaMA-Factory 👍 1 chenweilong915 commented Mar 6, 2024 I also met this problem. When I use the SFTTrainer with PEFT and save the model, it is the same for the original model and the trained model. When I ...
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pipeline("question-answering", model="smile367/task_qa_distilbert"),其中model参数指定远程的模型。 test_data=load_dataset("squad",split="validation[:1]")print("question: {}".format(test_data["question"]))print("context: {}".format(test_data["context"]))print("answers: {}".format(test...
pipeline 是diffusers 甚至huggingface各个库的一个重要概念,他封装了各个模型加载权重,构建网络结构,推理和训练的全部过程。 这里以stable diffusion 1.5为例,首先创建pipeline,并指明stable diffusion 的版本 fromdiffusersimportDiffusionPipeline model_id ="runwayml/stable-diffusion-v1-5"pipeline = DiffusionPipeline.fr...
models/.tar.gz:your initial model [2]查看NLU训练数据 nlu.md是训练rasa nlu模块的数据集。 [3]定义模型配置 主要是rasa nlu和rasa core的配置,比如language、pipeline、policies等。 [4]写第一个故事[Story] stories.md是训练rasa core模块的数据集。 [5]定义一个...
model_id = "runwayml/stable-diffusion-v1-5" pipeline = DiffusionPipeline.from_pretrained(model_id) 接下来给出提示(prompt) 代码语言:text 复制 prompt = "portrait photo of a old warrior chief" 为了加速推理,我们可以把数据放到gpu上 代码语言:text ...