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Newly published work from FAIR, Chameleon: Mixed-Modal Early-Fusion Foundation Models. This research presents a family of early-fusion token-based mixed-modal models capable of understanding & generating images & text in any arbitrary sequence. Paper ➡️ go.fb.me/7rb19n

I’m excited to announce our latest paper, introducing a family of early-fusion token-in token-out (gpt4o….), models capable of interleaved text and image understanding and generation. arxiv.org/abs/2405.09818

Meta presents Chameleon: Mixed-Modal Early-Fusion Foundation Models - SotA in image captioning - On par with Mixtral 8x7B and Gemini-Pro on text-only tasks - On par with Gemini Pro and GPT-4V on a new long-form mixed-modal generation evaluation arxiv.org/abs/2405.09818

Armen and team have been working in this direction for a while now, and I’ve been eagerly following from the sidelines since the CM3 paper. Very nice to see the line of work come to fruition! Also nice to see that QK-layernorm works beyond ViT-22B.

New work from FAIR exploring multimodal understanding and generation, all in a single model.

34B-sized model edges out the titans of multimodality 🧵📖 Read of the day, day 57: Chameleon: Mixed-Modal Early-Fusion Foundation Models, by Srini Iyer, Huang, Pasunuru et al from the FAIR team of AI at Meta arxiv.org/pdf/2405.09818 Current main vision language open source

Chameleon from Srini Iyer and Meta engineers is utterly fascinating for image generation from text only recipe! arxiv.org/abs/2405.09818…

I’m excited to share a few things we’re releasing today at Meta FAIR. These new AI model and dataset releases are part of our longstanding commitment to open science and I look forward to sharing even more work like this from the brilliant minds at FAIR! ai.meta.com/blog/meta-fair…

🚀 Exciting news! We're open sourcing Chameleon, our early fusion multimodal foundation model from last year. It handles multimodal inputs with text generation outputs, though it was trained for both text and image generation. #OpenSource #AI #ChameleonModel

🦎 Chameleon weights are out!

Extremely proud of the team who made it happen. Armen Aghajanyan Srini Iyer Luke Zettlemoyer Asli Celikyilmaz Victoria X Lin Scott Yih Lili Yu and many others!

Excited to see the open source release of FAIR's early fusion multimodal LLMs!

Lots of open source models released by Meta FAIR today: - Chameleon: experiment in vision-language model with early fusion. - LLM with multi-token prediction. - Joint Audio and Symbolic Conditioning for Temporally Controlled Text-to-Music Generation (JASCO). - AudioSeal: audio

Last week we released Meta Chameleon: a new mixed-modal research model from Meta FAIR. Get the models ➡️ go.fb.me/4m87kk The 7B & 34B safety tuned models we’ve released can take any combination of text and images as input and produce text outputs using a new early

Folks at GAIR-NLP have successfully managed to fine-tune image and interleaved generation back into Chameleon! Turns out, it’s quite hard to disable image generation out of early fusion models. Love all the example generations! Hope to see many more lizards!

Our MoMa paper is live! We show how we can significantly improve pre-training of fully mixed-modal early fusion models by using Mixture of Experts that are modality aware. We explore three dimensions of adaptive compute i.e. modalities, experts, and depths! Lots of learnings!

📣 Today we're opening a call for applications for Llama 3.1 Impact Grants! Until Nov 22, teams can submit proposals for using Llama to address social challenges across their communities for a chance to be awarded a $500K grant. Details + application ➡️ go.fb.me/smw6xc