Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
- fine-tuning
- llama
- llm
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Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
Open source software that helps you create and deploy high-frequency crypto trading bots
Official code for "F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching"
The official GitHub page for the survey paper "A Survey of Large Language Models".
An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)
Multi-user anti-filtering panel, with an effortless installation and supporting more than 20 protocols to circumvent filtering plus the telegram proxy.
Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM
Official release of InternLM series (InternLM, InternLM2, InternLM2.5, InternLM3).
TranslatedChinese LLaMA-2 & Alpaca-2 LLMs with 64K long context models
TranslatedStock AI Trader: 1-stop platform for learning, sim & live trading. Covers: stock basics, strategies, LLMs, factor mining, ML/DL/RL, graph nets, HFT, C++ deploy & JoinQuant code.
TranslatedTutorial on building a chatbot yourself
TranslatedMedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training Pipeline. Training medical large models, implementing incremental pre-training (PT), supervised fine-tuning (SFT), RLHF, DPO, ORPO, and GRPO.
OpenClaw-RL: Train any agent simply by talking
Robust recipes to align language models with human and AI preferences
Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more.
Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
The open source research environment for AI researchers to seamlessly train, evaluate, and scale models from local hardware to GPU clusters.
A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)
Align Anything: Training All-modality Model with Feedback
Resources to Prepare for Quant Developers/ Quantitative Researcher/ Quantitative Trader/ Quant Analyst/ Software Engineers in Quant Trading Firms, HFTs and Hedge Funds
A Doctor for your data
Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers.
An Efficient and User-Friendly Scaling Library for Reinforcement Learning with Large Language Models