Fine Tuning
Showing 23 of 23 projects
A web UI and optimization library for running and fine-tuning open-source AI models locally with 2x faster training and 70% less VRAM.
An open-source framework for building LLM-powered applications with data ingestion, indexing, and retrieval capabilities.
TensorFlow implementation and pre-trained models for BERT, a bidirectional Transformer for language understanding.
An open-source framework for financial large language models, enabling cost-effective fine-tuning for tasks like sentiment analysis and forecasting.
A comprehensive library for post-training foundation models using reinforcement learning and fine-tuning techniques.
Official JAX/Flax implementation of Vision Transformer (ViT) and MLP-Mixer for image recognition, with pre-trained models.
Unofficial Go client library for the OpenAI API, supporting ChatGPT, GPT-4, DALL·E, Whisper, and more.
A collection of libraries to optimize AI model performance through inference acceleration, infrastructure efficiency, and fine-tuning optimization.
A curated collection of resources for building, training, serving, and optimizing production-grade Large Language Model applications.
A free course teaching how to design, train, and deploy a production-ready real-time financial advisor LLM system using RAG and LLMOps.
A high-performance, scalable LLM library and reference implementation written in pure Python/JAX for training on TPUs and GPUs.
A JAX research toolkit for building, editing, and visualizing neural networks as legible, functional pytree data structures.
A Python package for fine-tuning and generating text with GPT-2 and GPT Neo models using PyTorch and Hugging Face Transformers.
An all-in-one framework for training state-of-the-art computer vision models, covering pretraining, fine-tuning, and distillation.
An open-source study on neural question generation using transformers, providing simplified training and inference pipelines.
A collection of TensorFlow tutorials and examples covering image classification, GANs, text classification, and model deployment.
A pretrained modeling library for Keras 3 offering simple, flexible, and fast access to models for text, image, and audio tasks.
Run ONNX transformer pipelines (like Hugging Face) natively in Go for inference and fine-tuning, with support for CPU, GPU, and TPU.
An enterprise-grade Graph RAG framework combining hierarchical tree navigation with knowledge graph reasoning for verifiable, on-premise AI.
A Python library that simplifies using, finetuning, and deploying state-of-the-art machine learning models for various AI tasks.
A collection of Python applications demonstrating various use cases of ChatGPT, including chatbots, automation, and voice assistants.
A JAX transform that implements LoRA (Low-Rank Adaptation) for efficient fine-tuning of large models with minimal memory overhead.
A zero-code desktop app for locally fine-tuning LLMs on Apple Silicon, with privacy-first data preparation and MLX-powered training.
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