ANOLE: An Open, Autoregressive, Native Large Multimodal Models for
  Interleaved Image-Text Generation
Previous open-source large multimodal models (LMMs) have faced several
limitations: (1) they often lack native integration, requiring adapters to
align visual representations with pre-trained large language models (LLMs); (2)
many are restricted to single-modal generation; (3) while some support
multimodal generation, they rely on separate diffusion models for visual
modeling and generation. To mitigate these limitations, we present Anole, an
open, autoregressive, native large multimodal model for interleaved image-text
generation. We build Anole from Meta AI's Chameleon, adopting an innovative
fine-tuning strategy that is both data-efficient and parameter-efficient. Anole
demonstrates high-quality, coherent multimodal generation capabilities. We have
open-sourced our model, training framework, and instruction tuning data.
668cf5f763d1bc005ba9d481
Ethan Chern
claimed_verified
2024-07-09T09:18:31.173Z
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Ethan Chern
user
ethanchern
668cf5f763d1bc005ba9d482
Jiadi Su
admin_assigned
2024-07-09T09:34:27.601Z
65437c82d3db5d5336af93ff
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Jiadi Su
user
JoyBoy-Su
668cf5f763d1bc005ba9d483
Yan Ma
claimed_verified
2025-05-26T08:50:18.966Z
633fc70529b5a95f6e15a6b7
https://cdn-avatars.huggingface.co/v1/production/uploads/633fc70529b5a95f6e15a6b7/Fzh7wWuqU-fBbzdupOUtF.jpeg
Yan Ma
user
ManTle
668cf5f763d1bc005ba9d484
Pengfei Liu
admin_assigned
2024-07-09T09:35:09.039Z
6144a0c4ff1146bbd84d9865
https://cdn-avatars.huggingface.co/v1/production/uploads/1661715958139-6144a0c4ff1146bbd84d9865.png
Pengfei Liu
user
Pengfei
ANOLE: An Open, Autoregressive, Native Large Multimodal Models for
  Interleaved Image-Text Generation
Previous open-source large multimodal models (LMMs) have faced several
limitations: (1) they often lack native integration, requiring adapters to
align visual representations with pre-trained large language models (LLMs); (2)
many are restricted to single-modal generation; (3) while some support
multimodal generation, they rely on separate diffusion models for visual
modeling and generation. To mitigate these limitations, we present Anole, an
open, autoregressive, native large multimodal model for interleaved image-text
generation. We build Anole from Meta AI's Chameleon, adopting an innovative
fine-tuning strategy that is both data-efficient and parameter-efficient. Anole
demonstrates high-quality, coherent multimodal generation capabilities. We have
open-sourced our model, training framework, and instruction tuning data.
Anole, an autoregressive large multimodal model based on Meta AI's Chameleon, supports efficient and high-quality interleaved image-text generation using native integration and an innovative fine-tuning strategy.
open-source multimodal models LMMs large language models LLMs diffusion models native integration autoregressive parameter-efficient fine-tuning