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Aligning pretrained language models with instruction data generated by themselves.
High-speed Large Language Model Serving for Local Deployment
[MLSys 2024 Best Paper Award] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
AutoAWQ implements the AWQ algorithm for 4-bit quantization with a 2x speedup during inference. Documentation:
Fast and memory-efficient exact attention
Accessible large language models via k-bit quantization for PyTorch.
Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
Inference code for Persimmon-8B
A distributed Spark/Scala implementation of the isolation forest algorithm for unsupervised outlier detection, featuring support for scalable training and ONNX export for easy cross-platform infere…
Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform
[ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings
Efficient few-shot learning with Sentence Transformers
Code and documentation to train Stanford's Alpaca models, and generate the data.
🦜🔗 Build context-aware reasoning applications
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and l…
Displaying Strava stats on a Inky Impressions e-ink display
Perform data science on data that remains in someone else's server
A Python package to assess and improve fairness of machine learning models.
NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft
MLOps using Azure ML Services and Azure DevOps
See what's happening on GitHub in real time (also helpful if you need to use up your API quota as quickly as possible)
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Flax is a neural network library for JAX that is designed for flexibility.
Mistral: A strong, northwesterly wind: Framework for transparent and accessible large-scale language model training, built with Hugging Face 🤗 Transformers.
🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support