# open-mmlab/Multimodal-GPT

Multimodal-GPT

Repository: https://github.com/open-mmlab/Multimodal-GPT
Canonical: https://ross.abutalabs.com/products/multimodal-gpt
Language: Python
License: Apache-2.0
License Family: permissive
Topics: flamingo, gpt, gpt-4, llama, multimodal, transformer, vision-and-language
Last push: 2023-06-04T01:42:37+00:00

## Health v2 (maintenance only)
Score: 30/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 87
- inputs: {"age_days": 1225, "days_push": 1187, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1512, forks 128 (observed 2026-08-28T04:04:56.009549+00:00)

## What it is
Multimodal-GPT is an open-source project for training a multimodal chatbot that combines vision and language instructions, built on OpenFlamingo. It jointly fine-tunes visual and language instruction data (VQA, captioning, visual reasoning, OCR, visual dialogue) using parameter-efficient LoRA tuning.

## Use cases
- train a multimodal chatbot that understands images and text
- fine-tune a vision-language model with LoRA
- build a visual question answering assistant
- jointly train on visual and language instruction data
- experiment with OpenFlamingo-based multimodal models
- create a GPT-4-style assistant that can see images

## When to choose
- you want to train or fine-tune an open multimodal vision-language chatbot
- you need LoRA-based parameter-efficient tuning of a Flamingo-style model
- you want to combine VQA, captioning, and dialogue instruction data in joint training

## When to avoid
- you need a production-ready multimodal assistant with active maintenance
- you want inference-only usage without training infrastructure
- you need the latest multimodal LLM capabilities, as the project has not been updated since mid-2023

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, llm-training, chatbot, nlp, computer-vision
- domain: artificial-intelligence, large-language-models, computer-vision, machine-learning
- platform: python
- tags: multimodal, vision-language, flamingo, lora, visual-instruction-tuning, openmmlab, natural-language-processing, gpu, linux

## Member repositories
- open-mmlab/Multimodal-GPT (main) score 30

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:56.009549+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 2026-08-30T04:32:20.424110+00:00, confidence not recorded.
  - readme: https://github.com/open-mmlab/Multimodal-GPT (fetched 2026-08-28T04:04:56.009549+00:00, sha 51f6d0a11fb8)
- Data as of 2026-08-30T08:39:29.467469+00:00.