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...
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...
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"])...
If you need more information regarding the topic, you can reply with what furhter information could help", ## add the description of what I want it to work on query_wrapper_prompt = "<|USER|>{query_str}<|ASSISTANT|>", tokenizer_name="meta-llama/Llama-2-7b-chat-hf", model_name="...
"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....
部署HF的应用到阿里云,应用地址:https://huggingface.co/spaces/huggingface-projects/llama-2-7b-chat[htt...
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.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin", "model.layers.2.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin", "model.layers.2.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin", "model.layers.2.self_attn.k_proj.weight"...
I am using huggingface transformer API and meta-llama/Llama-2-7b-chat-hf model to generate responses in an A100. I find out that it can generate response when the prompt is short, but it fails to generate a response when the prompt is long. ...