Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Large Language Models for All, 🦙 Cult and More, Stay in touch !
| Date | Stars |
|---|---|
| 2026-07-24 | 449 |
| 2026-07-25 | 449 |
| 2026-07-28 | 449 |
| 2026-07-30 | 449 |
| 2026-07-31 | 449 |
| 2026-08-06 | 449 |
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- Providing valuable insights into the latest models, including number of parameters, fine-tuning datasets and techniques, and hardware specifications. - Practical guides for LLM alignment post-training, include dataset, benchmark datasets, efficient training libraries and techniques; also involves short insight of pre-trained LLMs. - Explore from pre-training models to post-training models, interesting things you will get. ## Catalog - [Catalog](#catalog) - [Pre-trained Base Models](#pre-trained-base-models) - [Licences](#licences) - [Open Source Aligned LLMs](#open-source-aligned-llms) - [Instruction and Conversational Datasets](#instruction-and-conversational-datasets) - [Pre-training Datasets](#pre-training-datasets) - [Efficient Training](#efficient-training) - [Efficient Training Library](#efficient-training-library) - [Typology of Efficient](#typology-of-efficient) - [Evaluation Benchmark](#evaluation-benchmark) - [Multi-Modal LLMs](#multi-modal-llms) - [Tool Learning](#tool-learning) - [Star History](#star-history) ## Pre-trained Base Models <details><summary> Simple Version </summary> - OpenAI: GPT-1, GPT-2, GPT-3, InstructGPT, Code-davinci-002, GPT-3.5, GPT-4(-8k/32k) - Anthropic: Claude-v1, Claude Instant - Meta: OPT, Galactica, LLaMA - huggingface BigScience: BLOOM (176B), BLOOMZ, mT0 - EleutherAI: GPT-Neo, GPT-J (6B), GPT-NeoX (20B), Pythia - TogetherCompute: GPT-JT, RedPajama-7B, RedPajama-INCITE - Berkeley: OpenLLaMA - MosaicML: MPT-7B, MPT-7B-Instruct/Chat - TII: Falcon-7/40B-(instruct) - BlinkDL: RWKV-4-Pile, RWKV-4-PilePlus - Tsinghua THUDM: GLM-130B, ChatGLM-6B - Cerebras: Cerebras-GPT - Google: T5, mT5, LaMDA, Pathways, PaLM, UL2, Flan-T5, Flan-UL2, Bard, PaLM-E, PaLM 2, MoE, Switch Transformer, GLaM, ST-MoE, MoE Routing - DeepMind: Gopher, Chinchilla, Sparrow - Nvidia: Megatron-Turing NLG (530B) - AI21 Studio: Jurassic-1, Jurassic-2   - [LLMsPracticalGuide](https://github.com/Mooler0410/LLMsPracticalGuide) - [Awesome-LLM](https://github.com/Hannibal046/Awesome-LLM) - [GenAI_LLM_timeline](https://github.com/hollobit/GenAI_LLM_timeline) - [Open-LLMs](https://github.com/eugeneyan/open-llms) </details> - OpenAI - 2018/06, GPT-1 (117m) - 2019/02, GPT-2 (1.5B) - 2020/06, GPT-3 (175B): ada(350M), babbage(1.3B), curie(6.7B), davinci(175B), [detail here](https://learn.microsoft.com/en-us/azure/cognitive-services/openai/concepts/models) - 2022/01, InstructGPT-3: text-ada(350M), text-babbage(1.3B), text-curie(6.7B), text-davinci-001(175B) - 2022/02, Code-davinci-002 - [GPT-3.5](https://en.wikipedia.org/wiki/GPT-3#GPT-3.5) (175B): text-davinci-002 (2022/03), text-davinci-003 (2022/11), ChatGPT (2022/11), gpt-3.5-turbo (2023/03) - 2023/03, GPT-4(-8k/32k) - Anthropic - Claude-v1: 2023/03, state-of-the-art high-performance model, context window 9k/100k tokens - Claude Instant: 2023/03, lighter, less expensive, and much faster option, context window 9k/100k tokens - Meta - OPT (125M/350M/1.3B/2.7B/6.7B/13B/30B/66B/175B): 2022/03, pre-trained on (datasets used in RoBERTa, the Pile, `PushShift.io` Reddit) using [metaseq](https://github.com/facebookresearch/metaseq), 1/7th the carbon footprint if GPT-3, combining Meta’s open source Fully Sharded Data Parallel (FSDP) API and NVIDIA’s tensor parallel abstraction within Megatron-LM, contain predominantly English text and a small amount of non-English data via CommonCrawl, [released](https://huggingface.co/models?search=facebook/opt) under a [noncommercial](https://ai.facebook.com/blog/democratizing-access-to-large-scale-language-models-with-opt-175b/) license. - [OPT-IML](https://huggingface.co/facebook/opt-iml-30b) (30B/175B): 2022/12, create OPT-IML Bench, a
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matched fp:bd890460dbb7091b, topic:pytorch, topic:tensorflow, topic:deepspeed
matched fp:bd890460dbb7091b, topic:llm, topic:gpt, topic:llama