config.model_type = "llama" _optimize_pre(model.llm, qtype=qtype) model.llm.config.model_type = "minicpmv" return model @@ -933,16 +937,6 @@ def _optimize_ipex(model, qtype=ggml_tensor_qtype["bf16"]): def _optimize_post(model, lightweight_bmm=False): from packaging import ...
pip install git+https://github.com/huggingface/transformerscd transformerspython convert_llama_weights_to_hf.py \ --input_dir /path/to/downloaded/llama/weights --model_size 7B --output_dir models_hf/7B 现在,我们得到了一个Hugging Face模型,可以利用Hugging Face库进行微调了! 3. 运行微调笔记本: ...
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. - transformers/src/transformers/models/llama/convert_llama_weights_to_hf.py at main · huggingface/transformers
logger.info("Usage: python convert_hf_to_gguf_update.py <huggingface_token>") sys.exit(1) else: logger.info("Usage: python convert_hf_to_gguf_update.py <huggingface_token>") sys.exit(1) # TODO: add models here, base models preferred models = [ {"name": "llama-spm",...
"Path must contain HuggingFace PEFT LoRA files 'adapter_config.json' and 'adapter_model.bin'" ) print(f"Arch must be one of {list(gguf.MODEL_ARCH_NAMES.values())} (default: llama)") sys.exit(1) input_json = os.path.join(sys.argv[1], "adapter_config.json") input_model =...
如需使用DeepGPU-LLM对其他开源LLM模型进行推理优化,您需要先将huggingface格式的开源模型转换为DeepGPU-LLM支持的格式,然后才能使用DeepGPU-LLM进行模型的推理优化服务。以qwen-7b-chat为例,您可以使用以下命令在容器中进行模型格式... Linux系统常用命令 B 输出前将块大小转换为指定大小。h以 1024 为幂显示大小(...
I was trying to convert EverythingLM V2 with 16k context to GGUF and noticed that it generated nonsense. GGUF metadata showed that the rope scale was not kept, and I see it was indeed not read from...
Hi team, I have seen that the Phi vision model is avalible I would like to request if you could convert the Llama 3.2 vision model and the other Llama model to 3.2 to as well. https://huggingface.co/meta-llama/Llama-3.2-11B-Vision-Instruct/tree/main thanks...
choices=['baichuan', 'baichuan2', 'llama2', 'mixtral', 'chatglm3', 'gemma', 'gemma2', 'bloom', 'qwen', 'internlm2', 'deepseek2', 'minicpm', 'minicpm3', 'minicpm-moe', 'deepseek2-lite', 'qwen2-moe', 'phi3.5'], help='model type of huggingface') parser.add_arg...
help = 'Default max context length: LLaMA1 is typically 2048, LLaMA2 is typically 4096') parser.add_argument('--model-metadata-dir', '-m', type = Path, help ='Load HuggingFace/.pth vocab and metadata from the specified directory') parser.add_argument("--vocab-dir", type=Path, ...