# 加载模型和分词器 model_path = '/data04/llama3/Meta-Llama-3.1-8B-Instruct' tokenizer = AutoTokenizer.from_pretrained(model_path) model = AutoModelForCausalLM.from_pretrained( model_path, low_cpu_mem_usage=True, qua
mlc-llm python mlc_llm quantization group_quantization.py onmain User selector All users DatepickerAll time Commit History Commits on Jun 12, 2024 [Model] Enhance error reporting for invalid tensor-parallel settings (#2566) MasterJH5574committedJun 12, 2024 · 3 / 3 Verified 873827c Commits ...
# Dispatch quantization scheme # Also see https://github.com/mlc-ai/mlc-llm/blob/main/mlc_llm/quantization/__init__.py for name in parameter_names: if "norm.weight" not in name and "embed" not in name: param_map[name] = [f"{name}_quantized", f"{name}_scale"] map_func[name]...
Deep Learning with Low Precision by Half-wave Gaussian Quantization Zhaowei Cai, Xiaodong He, Jian Sun, Nuno Vasconcelos Computer Vision and Pattern Recognition (CVPR), 2017 (spotlight) | July 2017 Publication Publication Semantic Compositional Networks for Visual Captioning Zhe Gan, Chuang Gan...
There exist many alternative clustering methods, such as the hierarchical clustering, self-organizing map, tree-truncated vector quantization method, among others. For data sets with unknown data structures, there exists no dominating approach. We use the K-means approach since it is computationally ...
Sci. 2023, 13, 9676 100 images, this study employs a non-uniform quantization method to process the H, S, and V channels, reducing the excessive dimensionality of the feature vector and improv5ionfg17 the efficiency of classifier construction and recognition accuracy. In the experiment, H, S...
VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models Yifei Liu, Jicheng Wen, Yang Wang, Shengyu Ye, Li Lyna Zhang, Ting Cao, Cheng Li, Mao Yang November 2024 Publication Github SeerAttention: Learning Intrinsic Sparse Attention in Your LLMs Yizhao Gao, Zhi...
LLMTools: Run & Finetune LLMs on Consumer GPUs LLMTools is a user-friendly library for running and finetuning LLMs in low-resource settings. Features include: 🔨 LLM finetuning in 2-bit, 3-bit, 4-bit precision using the LP-LoRA algorithm 🐍 Easy-to-use Python API for quantization,...
LLM long text based on transformers structure requires more memory. At this time, kv cache quantization needs to be done on the model, such aslmdeploy quantization description. Then use docker to independently deploy Hybrid LLM Service. No module named 'faiss.swigfaiss_avx2' ...
VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models Yifei Liu, Jicheng Wen, Yang Wang, Shengyu Ye, Li Lyna Zhang, Ting Cao, Cheng Li, Mao Yang November 2024 Publication Github Anatomizing Deep Learning Inference in Web Browsers Qipeng Wang, Shiqi Jiang, ...