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natural-language-processing x

5 search results found

Chinese Llama Alpaca ⭐ 15,877

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

Autogptq ⭐ 3,637

An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.

Nlp Architect ⭐ 2,928

A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks

Deepsparse ⭐ 2,729

Sparsity-aware deep learning inference runtime for CPUs

Neural Network Compression Framework for enhanced OpenVINO™ inference

Complete Life Cycle Of A Data Science Project ⭐ 499

Complete-Life-Cycle-of-a-Data-Science-Project

Squeezellm ⭐ 486

SqueezeLLM: Dense-and-Sparse Quantization

Sparsezoo ⭐ 347

Neural network model repository for highly sparse and sparse-quantized models with matching sparsification recipes

⚡ boost inference speed of T5 models by 5x & reduce the model size by 3x.

Compress Fasttext ⭐ 153

Tools for shrinking fastText models (in gensim format)

Great Deep Learning Tutorials ⭐ 153

A Great Collection of Deep Learning Tutorials and Repositories

Compact high quality word embeddings for Russian language

Bert Squeeze ⭐ 77

🛠️ Tools for Transformers compression using PyTorch Lightning ⚡

Fasttext.netwrapper ⭐ 60

.NET Standard wrapper for fastText library. Now works on Windows, Linux and MacOs!

Roy: A lightweight, model-agnostic framework for crafting advanced multi-agent systems using large language models.

Offline semantic Text-to-Image and Image-to-Image search on Android powered by quantized state-of-the-art vision-language pretrained CLIP model and ONNX Runtime inference engine

[ICML'21] I-BERT: Integer-only BERT Quantization

Neurips Micronet ⭐ 29

[JMLR 2020] NeurIPS 2019 MicroNet Challenge Efficient Language Modeling, Champion

Embeddings.js ⭐ 23

Word embeddings for the web

Optimum Openvino ⭐ 8

Intel OpenVINO extension for Hugging Face Transformers

Something in the middle of Karpathy's mingpt model and video lectures, BabyGPT is an easy to use model on a much smaller scale (16 and 256 out channels , 5 heads, fine tuned). To be made useful on low powered devices.

Comprehensive LLMs repo, where I cover both theoretical and practical aspects of LLMs.

Memory-mapped word embeddings storage with quantization support

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1-5 of 5 search results

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