Open-Source Training and RLHF Frameworks
Frameworks for pretraining, distributed training and reinforcement learning, including DeepSpeed, verl and nanoGPT.
LLM training framework with ready-made research scripts, NVIDIA GPU parallelism, and Hugging Face checkpoint conversion through Megatron Bridge.
18KUpdated 1 day ago
Docker#Distributed execution#Hugging Face integration#Quantization
Megatron-LM is a Python framework for research teams training large language models on NVIDIA GPU infrastructure. It pairs ready-made training scripts with Megatron Core, a library developers can use to build their own training systems. Its focus is distributed training, with benchmarks on H100 clusters spanning thousands of GPUs.
LLM Libraries and SDKsQuantization and Model ConversionTraining Frameworks+0
An open-source Python library for adapting LLMs and diffusion models with less memory and storage, under Apache 2.0.
21.7KUpdated 1 day agoApache-2.0
macOS#Distributed execution#Hugging Face integration#LoRA
PEFT is an open-source Python library for developers who want to adapt pretrained models on their own hardware with less compute and storage than full fine-tuning requires. It trains a small subset of parameters, often through adapters, while leaving the base model intact. It's licensed under Apache 2.0.
LLM Fine-TuningLoRA and Image Model TrainingTraining Frameworks+0
An open source AI platform for Kubernetes that supports self-hosted ML workflows, distributed training and model management under Apache 2.0.
15.9KUpdated 1 month agoApache-2.0
Web#MLX#Multi-user access
Kubeflow is a self-hosted AI platform for teams that run machine learning workloads on Kubernetes. It brings model development, training and production workflows into a modular stack that can run on a local laptop, on-premises infrastructure or a cloud Kubernetes cluster. It's open source under Apache 2.0.
Experiment Tracking and MLOpsKubernetes and Cloud-Native AILLM Fine-TuningTraining Frameworks+0
Apache 2.0 LLM fine-tuning framework for local or cloud GPUs, supporting NVIDIA, AMD, LoRA, QLoRA and multimodal training.
12.5KUpdated 2 days agoApache-2.0
Docker#Distributed execution#Hugging Face integration#LoRA
Axolotl is an open-source LLM fine-tuning framework for developers, researchers, and teams training models on their own data. It runs on local hardware or cloud infrastructure you control, including Docker and Kubernetes environments. The framework uses Apache 2.0, which permits commercial use.
LLM Fine-TuningQuantization and Model ConversionTraining Frameworks+0
Open-source text-to-speech toolkit for local speech generation, voice cloning and model training on Linux, macOS and Windows, licensed under MPL-2.0.
2.3KUpdated 4 months agoMPL-2.0
macOS · Windows · Linux · Docker#Multilingual#Streaming inference#Voice cloning
Coqui TTS (idiap fork) is a local text-to-speech library for developers and speech researchers who want pretrained voices or tools to train their own models. It builds on coqui-ai/TTS, continuing the original unmaintained project. The Python toolkit is open source under the Mozilla Public License 2.0 (MPL-2.0).
Inference Libraries and BindingsText-to-Speech and AudiobooksTraining FrameworksVoice Cloning and Voice Changers+0
A PyTorch library for training and inference on local machines or clusters, with CPU, GPU and TPU support. Open source under Apache 2.0.
9.9KUpdated 1 day agoApache-2.0
#Distributed execution
Accelerate is a Python library for developers and researchers who write their own PyTorch training loops and want to use the same code on a local machine or a distributed cluster. It handles the hardware-specific work while leaving the training logic under your control.
GPUs, Clusters and EdgeInference Libraries and BindingsTraining Frameworks+0
Open-source computer vision library for local detection, segmentation and tracking, with AGPL-3.0 licensing and exports to ONNX, TensorRT and CoreML.
62.1KUpdated 24 hours agoAGPL-3.0
#ONNX
Ultralytics YOLO is an open-source Python computer vision library for developers building applications that analyze images and video on their own hardware. It supports local and edge deployment, including NVIDIA Jetson, Raspberry Pi and mobile phones. A separate hosted platform provides browser-based annotation, cloud GPU training and managed prediction endpoints.
Computer Vision ModelsEdge and Embedded AIInference Libraries and BindingsTraining Frameworks+0
Python library for running and training embedding and reranker models locally, with Apache 2.0 licensing and pretrained models on Hugging Face.
19.1KUpdated 1 week agoApache-2.0
#Hugging Face integration#Multilingual#Multimodal input
Sentence Transformers is an open-source Python library for developers building semantic search and document retrieval on their own hardware. It runs embedding and reranker models locally, turning content into numerical representations for similarity comparisons and scoring results against a query. The library uses the Apache 2.0 license.
Inference Libraries and BindingsRAG and Vector SearchTraining Frameworks+0
Open-source Rust ML framework for running models locally on CPUs, NVIDIA GPUs or in browsers, with Apache 2.0 licensing and quantized LLM support.
21.1KUpdated 2 days agoApache-2.0
macOS · Web#GGUF#Hugging Face integration#Multilingual
Candle is a Rust machine learning framework for developers who want to embed local AI in applications or deploy models on their own servers. It produces lightweight binaries that don't need Python in production, making it a candidate for serverless inference where a large runtime can slow startup. Its API uses tensor operations familiar to PyTorch developers.
Inference Libraries and BindingsOn-Device and In-Browser AITraining Frameworks+0
