部署llama2-7b-chat-hf模型(CPU版本)需要按照以下步骤进行: 获取模型:首先,您需要从GitHub上获取llama2-7b-chat-hf模型的代码仓库。可以使用git clone命令来克隆或下载代码仓库,例如:git clone <repository_url>。请将<repository_url>替换为实际的代码仓库URL。 安装依赖:进入代码仓库所在的文件夹,然后执行安装依赖...
The error is as below: Traceback (most recent call last): File "/home/jwang/ipex-llm-jennie/python/llm/example/CPU/HF-Transformers-AutoModels/Model/llama2/./generate.py", line 65, in output = model.generate(input_ids, File "/root/anaconda3/envs/jiao-llm/lib/python3.9/site-packages/...
-LLaMA 2与RLHF的调谐有可能增强模型的操纵性。 -有些HuggingFace模型是使用Apache或BSD许可证的开源。 -量化和微调可在A40或RTX3090等GPU上执行。 -LLaMA型号与DeepSpeed-Cap兼容,可用于训练和发球。 -llama.cpp存储库支持以GGML格式运行llama模型。 -OIG数据集适用于LLaMA模型微调。 -FastChat和Oobabooga是支持...
from_pretrained("meta-llama/Llama-2-7b-chat-hf", use_fast=False) llama2 = models.TogetherAI("meta-llama/Llama-2-7b-chat-hf", tokenizer, echo=False) with user(): llama2 += f'what is your name? ' with assistant(): llama2 += gen("answer", stop='.') print(llama2["answer"])...
我正在运行的代码是:进口火炬从 llama_index.llms.huggingface 导入 HuggingFaceLLM llm = HuggingFaceLLM( 上下文窗口=4096, 最大新令牌=256, 生成_kwargs={"
"model.layers.2.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin", "model.layers.2.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin", "model.layers.2.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00002.bin", "model.layers.2.self_attn.v_proj...
部署HF的应用到阿里云,应用地址:https://huggingface.co/spaces/huggingface-projects/llama-2-7b-chat git clone后的文件: [图片上传失败...(image-5bb143-1705841574674)] 在阿里云PAI,申请DSW使用期GPU资源。 [图片上传失败...(image-a8dcd4-1705841741227)]...
2023-11-26 07:45:38 | ERROR | stderr | huggingface_hub.utils._validators.HFValidationError: Repo id must be in the form 'repo_name' or 'namespace/repo_name': '/mnt/d/llmbak/llama-2-7b-chat-hf-chinese/1.1'. Use `repo_type` argument if needed. 或者:HFValidationError: Repo id ...
"model.layers.2.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin", "model.layers.2.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin", "model.layers.2.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin", "model.layers.2.self_attn.rotary_emb....
BASE_MODEL = “meta-llama/Llama-2-7b-chat-hf” model = AutoModelForCausalLM.from_pretrained(BASE_MODEL, torch_dtype = “auto”, device_map=‘auto’) tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL) prompt = [{“role”: “user”, “content”: “To ensure the AI chatbots to promo...