fairseq2 retweeted
🚀New from Meta FAIR: today we’re introducing Seamless Interaction, a research project dedicated to modeling interpersonal dynamics.
The project features a family of audiovisual behavioral models, developed in collaboration with Meta’s Codec Avatars lab + Core AI lab, that wo individuals into diverse, expressive full-body gestures and active listening behaviors, allowing the creation of fully embodied avatars in 2D and 3D.
These models have potential to create more natural, interactive virtual agents that can engage in human-like social interactions across a variety of settings.
Learn more: ai.meta.com/research/seaml…
The project features a family of audiovisual behavioral models, developed in collaboration with Meta’s Codec Avatars lab + Core AI lab, that wo individuals into diverse, expressive full-body gestures and active listening behaviors, allowing the creation of fully embodied avatars in 2D and 3D.
These models have potential to create more natural, interactive virtual agents that can engage in human-like social interactions across a variety of settings.
Learn more: ai.meta.com/research/seaml…
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[1/4] 🛠️ FAIRSeq2 – your go-to tool for reliable benchmarking and diagnosing infra issues! With native logging of metrics, monitor training performance in real-time and ensure great visibility. #AI #MachineLearning #fairseq2
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[3/4] Beyond TensorBoard and WanDB, FAIRSeq2 supports torch profilers (set trainer.profile and common.profilers.torch.enabled=True) to inspect potential infra issues. Dive deep into your training processes with various profilers and metric recorders.
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[4/4] Collaborate efficiently with reproducible experiment setups using FAIRSeq2. Identify root causes swiftly and share lessons learned with the community. Create your benchmarks and contribute!
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🚀 Transform your LLM post-training with fairseq2! We make complex post-training into a breeze, so that you can make fairseq2 your paper machine!
Feel free to check our tutorials out:
- SFT: facebookresearch.github.io/fairseq2/stabl…
- DPO: facebookresearch.github.io/fairseq2/stabl…
Feel free to check our tutorials out:
- SFT: facebookresearch.github.io/fairseq2/stabl…
- DPO: facebookresearch.github.io/fairseq2/stabl…
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🚀 Big news for LLM researchers! #fairseq2 now has native support in @vllm_project. Deploy your fine-tuned language models with #vLLM in just one command for lightning-fast performance. Ready to accelerate your research like in @AIatMeta ? Check this out: facebookresearch.github.io/fairseq2/stabl…
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@vllm_project @AIatMeta Nothing explains better than a vivid example:
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Seamless Communication as the best innovation recognized by TIMES and Nature -- check it out here: ai.meta.com/research/seaml…
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Large Concept Models demonstrates what we can imagine beyond traditional sequence models -- check it out here: ai.meta.com/research/publi…
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👋 Hello world! We’re thrilled to announce the v0.4 release of fairseq2 — an open-source library from FAIR powering many projects at Meta. pip install fairseq2 and explore our trainer API, instruction & preference finetuning (up to 70B), and native vLLM integration.
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Check out our doc for more details: facebookresearch.github.io/fairseq2/stabl…
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