Python 排行榜

Tool-native dataset generation skill for Codex, Claude Code, and Antigravity with SFT/DPO pipelines, verification, deduplication, and flexible export.

Implementation of build an LLM from scratch by Sebastian Raschka.

⚡ A seamless integration of HuggingFace Transformers & Diffusers with RBLN SDK for efficient inference on RBLN NPUs.

🚀 Unified NLP Pipelines for Language Models

a smol tool for managing local models

The elegant integration of huggingface/nlp and fastai2 and handy transforms using pure huggingface/nlp

Comprehensive, scalable ML inference architecture using Amazon EKS, leveraging Graviton processors for cost-effective CPU-based inference and GPU instances for accelerated inference. Guidance provides a complete end-to-end platform for deploying LLMs with agentic AI capabilities, including RAG and MCP

A collection of simple transformer based chatbots.

Knowledge base Q&A program using LangChain for retrieval-augmented prompting and PGVector as vector store.

RAG system with real-time news scraping built using mixtral-8x7b, ChromaDB, bart summarizer

huggingface dataset with remote download support

Train a SmolLM-style llm on fineweb-edu in JAX/Flax with an assortment of optimizers.

MultimodalHugs is an extension of Hugging Face that offers a generalized framework for training, evaluating, and using multimodal AI models with minimal code differences, ensuring seamless compatibility with Hugging Face pipelines.

Llava, Ollama and Streamlit | Create POWERFUL Image Analyzer Chatbot for FREE - Windows & Mac

My own playground for PLP (Programming Language Processing) using DeepLearning techniques

Perform visual question answering on your images

Bringing some SQL to Qdrant

Vector compression with TurboQuant codecs for embeddings, retrieval, and KV-cache. 10x compression, pure NumPy core — optional GPU acceleration via PyTorch (CUDA/MPS) or MLX (Metal).

A Python SDK for OceanBase Multimodal Store—enabling vector search, full-text search, and JSON table operations—offers both Milvus-compatible API and SQLAlchemy-based SQL mode, and supports both OceanBase and OceanBase seekdb.

Turn your Google Search Console data into a vector database and analyze search performance with AI (Gemini, Grok, Claude)