⚡ Pure-Rust WebGPU inference engine — OpenAI-API compatible, GGUF native, runs on any GPU. No Python. No llama.cpp. Single binary.

A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines

Chronos: Pretrained Models for Time Series Forecasting

Structured data extraction, instruction calling and agentic workflows with ML, LLM and Vision LLM

Intelligent Mixture-of-Models Router for Efficient Heterogeneous LLMs Inference

中文nlp解决方案(大模型、数据、模型、训练、推理)

🧠💬 Articles I wrote about machine learning, archived from MachineCurve.com.

Social networking platform with automated content moderation and context-based authentication system

Label, clean and enrich text datasets with LLMs.

[CVPR 2025] Official PyTorch Implementation of MambaVision: A Hybrid Mamba-Transformer Vision Backbone

Simple UI for LLM Model Finetuning

a fast and user-friendly runtime for transformer inference (Bert, Albert, GPT2, Decoders, etc) on CPU and GPU.

Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using ⚡ Pytorch Lightning and 🤗 Transformers. For access to our API, please email us at contact@unitary.ai.

Pocket-Sized Multimodal AI for content understanding and generation across multilingual texts, images, and 🔜 video, up to 5x faster than OpenAI CLIP and LLaVA 🖼️ & 🖋️

Transformer models from BERT to GPT-4, environments from Hugging Face to OpenAI. Fine-tuning, training, and prompt engineering examples. A bonus section with ChatGPT, GPT-3.5-turbo, GPT-4, and DALL-E including jump starting GPT-4, speech-to-text, text-to-speech, text to image generation with DALL-E, Google Cloud AI,HuggingGPT, and more

Learn Cloud Applied Generative AI Engineering (GenEng) using OpenAI, Gemini, Streamlit, Containers, Serverless, Postgres, LangChain, Pinecone, and Next.js

Serverless LLM Serving for Everyone.

Multimodal model for text and tabular data with HuggingFace transformers as building block for text data

multilspy is a lsp client library in Python intended to be used to build applications around language servers.

[EMNLP 2022] Unifying and multi-tasking structured knowledge grounding with language models