Raner模型可以使用AutoModel的方式加载。AutoModel是阿里云ModelScope提供的一种自动化模型部署工具，它可以帮助用户快速创建、部署和管理模型。您试一下model = Model.from_pretrainedhttps://www.modelscope.cn/docs/%E5%8A%A0%E8%BD%BD%E6%A8%A1%E5%9E%8B%E5%92%8C%E9%A2%84%E5%A4%84%E7%90%86%E5%99%A8——此回答整理自钉群：魔搭ModelSco...
参考文档model = AutoModel.from_pretrained("hfl/rbt3",cache_dir='D:/Users/Desktop/aigc/cache/r...
from decord import VideoReader, cpu # pip install decord params={} model = AutoModel.from_pretrained('OpenBMB/MiniCPM-V-2_6-int4', trust_remote_code=True) # sdpa or flash_attention_2, no eager model = model.eval() tokenizer = AutoTokenizer.from_pretrained('OpenBMB/MiniCPM-V-2_6-in...
from modelscope import AutoModelForSequenceClassification, AutoTokenizer from swift import Trainer, LoRAConfig, Swift model = AutoModelForSequenceClassification.from_pretrained( 'AI-ModelScope/bert-base-uncased', revision='v1.0.0') tokenizer = AutoTokenizer.from_pretrained( 'AI-ModelScope/bert-base-un...
frommodelscopeimportAutoModel,AutoTokenizer# 下载模型和分词器model=AutoModel.from_pretrained('modelscope/xxx-model')tokenizer=AutoTokenizer.from_pretrained('modelscope/xxx-tokenizer')# 输入数据text="Hello, ModelScope!"inputs=tokenizer(text,return_tensors="pt")# 进行推理outputs=model(**inputs)print...
from transformers import AutoModel # 加载转换后的模型 model = AutoModel.from_pretrained('path_to_your_converted_model') # 验证模型(例如,通过进行推理) inputs = tokenizer("Hello, world!", return_tensors="pt") outputs = model(**inputs) print(outputs) 5. (可选)优化和调整模型以适应Hugging...
model = AutoModelForCausalLM.from_pretrained( model_dir, torch_dtype=torch.bfloat16, device_map="auto" ) # 配置LoRA lora_config = LoraConfig( r=8, lora_alpha=32, target_modules=["q_proj", "v_proj"], lora_dropout=0.05, task_type="CAUSAL_LM" ...
model = AutoModelForCausalLM.from_pretrained("./AI-ModelScope/CodeLlama-7b-Instruct-hf", pad_token_id=tokenizer.eos_token_id).to(device) prompt_text = "How are you ?" input_ids = tokenizer.encode(prompt_text, return_tensors="pt").to(device) ...
如果我将from modelscope import AutoModelForCausalLM, AutoTokenizer注释掉,就不会报错。 我怀疑是from modelscope import AutoModelForCausalLM, AutoTokenizer中修改了查找默认缓存模型路径,导致不会去~/.cache/huggingface中去查找模型权重,而是只会在~/.modelscope中查找。
是的，你可以使用transformers库来加载ModelScope下载的通用检查点。你需要使用AutoModel.from_pretrained()...