load_in_8bit=True, device_map='auto') 注:代码中我已经将模型cache到指定目录中,每次运行不用再从云端下载模型,但是为啥会调用hugggingface.co服务呢,我从源码看下,本地cache目录文件,这是transformers库,自动存放的,/root/.cache/huggingface/modules/transformers_modules/THUDM/chatglm-6b,这里面会存在模型相...
model = AutoModelForSeq2SeqLM.from_pretrained(model_id, load_in_8bit=True, device_map="auto") 现在,我们可以使用 peft 为LoRA int-8 训练作准备了。 from peft import LoraConfig, get_peft_model, prepare_model_for_int8_training, TaskType # Define LoRA Config lora_config = LoraConfig( r=...
from peft import PeftModel from transformers import LlamaTokenizer, LlamaForCausalLM, GenerationConfig model_name = "decapoda-research/llama-7b-hf" tokenizer = LlamaTokenizer.from_pretrained(model_name) model = LlamaForCausalLM.from_pretrained( model_name, load_in_8bit=True, device_map="auto", ...
device_map="auto"doesn't use all available GPUs whenload_in_8bit=True#22595 New issue System Info transformersversion: 4.28.0.dev0 Platform: Linux-4.18.0-305.65.1.el8_4.x86_64-x86_64-with-glibc2.28 Python version: 3.10.4 Huggingface_hub version: 0.13.3 ...
load_in_8bit=True, device_map="auto", ) pipeline = transformers.pipeline( "text-generation", model=model, tokenizer=tokenizer, ) 需要注意的是,INT8 混合精度推理使用的浮点精度是torch.float16而不是torch.bfloat16,因此请务必详尽地对结果进行测试。
pipeline = pipeline("text-generation", model=model, model_kwargs={"torch_dtype": torch.bfloat16,"quantization_config": {"load_in_4bit": True} },)有关使用 Transformers 模型的更多详细信息，请查看模型卡。模型卡https://hf.co/gg-hf/gemma-2-9b 与 Google Cloud 和推理端点的集成 ...
quantization_config = BitsAndBytesConfig(load_in_8bit=True, llm_int8_enable_fp32_cpu_offload=True) AutoModelForCausalLM.from_pretrained(path, device_map='auto', quantization_config=quantization_config) If the model does not fit into VRAM, it reports: ...
将load_in_8bit或load_in_4bit参数添加到from_pretrained()中,并设置device_map="auto"以有效地将模型分发到硬件: AI检测代码解析 from transformers import AutoModelForCausalLM, AutoTokenizer peft_model_id = "ybelkada/opt-350m-lora" model = AutoModelForCausalLM.from_pretrained(peft_model_id, ...
8 9 10 11 12 13 登陆后复制Assistant:1.在BIOS中,选择“Advanced BIOS Features”;2.在“Advanced Features”中,选择“System Configuration”,然后在“System Configuration”中选择“Advanced System Configuration”。3.在“Advanced System Configuration”中,选择“XMP”选项。4.点击“OK”。
from huggingface_hub import ( ImportError: cannot import name 'CommitOperationAdd' from 'huggingface_hub' (unknown location) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 解决方式: 1.