Awesome Open Source AI
Section: 7. Training & Fine-tuning Ecosystem · YAML-driven full pipeline for SFT, DPO, GRPO.
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Appears in 4 awesome lists
Axolotl is a tool designed to streamline the fine-tuning of various AI models, offering support for multiple configurations and architectures.
Section: 7. Training & Fine-tuning Ecosystem · YAML-driven full pipeline for SFT, DPO, GRPO.
Section: Model Training and Orchestration · Axolotl is a tool designed to streamline the fine-tuning of various AI models, offering support for multiple configurations and architectures.
Section: AI and Agents · A framework for fine-tuning and post-training large language models.
Section: Other · Go ahead and axolotl questions
Langchain integrates various providers like Anthropic, AWS, and OpenAI, and offers tools for components such as LLMs, chat models, and data analysis, supporting functionalities from Alpha Vantage to YouTube github | docs
Unified proxy and SDK that routes to 100+ LLM providers behind a single OpenAI-compatible interface, with a Router handling retry/fallback across deployments, per-project cost and rate-limit tracking, and OTEL callback integrations. The right infrastructure layer when your harness needs provider…
(formerly known as pytorch-transformers and pytorch-pretrained-bert) provides state-of-the-art general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet, CTRL...) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in…
(MIT) provides modules for structured outputs at different levels of abstraction, including output parsers for text completion endpoints, Pydantic programs for mapping prompts to structured outputs using function calling or output parsing, and pre-defined Pydantic programs for specific output types.
(from Hpcaitech) - A Unified Deep Learning System for Large-Scale Parallel Training (1D, 2D, 2.5D, 3D and sequence parallelism, and ZeRO protocol).
Mem0 is an intelligent memory layer for Large Language Models that enhances personalized AI experiences by retaining and utilizing contextual information across various applications. github | website | docs | discord | twitter | github profile | linkedin
A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library. ray.io
June 2026 harness-first redesign built around the Capability primitive: a single composable unit bundling instructions, tools, lifecycle hooks, and model settings. The split between a small stable core and a fast-moving pydantic-ai-harness lets capabilities graduate as they prove essential, while…