# InternLM/InternLM

Official release of InternLM series (InternLM, InternLM2, InternLM2.5, InternLM3).

Repository: https://github.com/InternLM/InternLM
Canonical: https://ross.abutalabs.com/products/internlm
Homepage: https://internlm.readthedocs.io/
Language: Python
License: Apache-2.0
License Family: permissive
Topics: chatbot, gpt, large-language-model, long-context, rlhf, fine-tuning-llm, llm, chinese, flash-attention, pretrained-models
Last push: 2025-10-30T00:35:43+00:00

## Health v2 (maintenance only)
Score: 41/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 49, release rhythm 8, longevity 82
- inputs: {"age_days": 1154, "days_push": 308, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 7269, forks 509 (observed 2026-08-28T04:09:57.929869+00:00)

## What it is
Official repository for the InternLM series of open-source large language models (InternLM, InternLM2, InternLM2.5, InternLM3), including pretrained and chat-tuned weights and training tooling. InternLM3-8B-Instruct targets general-purpose use and advanced reasoning with deep-thinking chain-of-thought mode.

## Use cases
- download and run an open-source 8B chat LLM locally
- fine-tune a large language model with RLHF
- run a bilingual Chinese-English instruction model
- evaluate reasoning-capable open LLMs against Llama or Qwen
- self-host a chatbot backed by an open-weights model
- train an LLM with long-context support and flash attention

## When to choose
- you need open-weights LLMs with strong Chinese-language capability
- you want to fine-tune or do RLHF on a permissively licensed (Apache-2.0) model
- you need a small-to-mid size model with deep reasoning / chain-of-thought modes

## When to avoid
- you only need an inference server for third-party models rather than model weights and training code
- you need the largest frontier-scale models
- you lack GPU hardware for training or local inference

## Facets
- artifact type: library
- maturity: active
- function: llm-training, llm-inference, machine-learning, deep-learning
- domain: large-language-models, artificial-intelligence
- platform: python
- tags: chatbot, rlhf, fine-tuning, long-context, flash-attention, chinese, pretrained-models, open-weights, natural-language-processing, gpu, linux, docker

## Member repositories
- InternLM/InternLM (main) score 41

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:57.929869+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:38:55.568338+00:00, confidence not recorded.
  - readme: https://github.com/InternLM/InternLM (fetched 2026-08-28T04:09:57.929869+00:00, sha 7eb23ebf2db5)
- Data as of 2026-08-30T08:39:29.467469+00:00.