Can Balioglu
@cbalioglu.bsky.social
Reposted by Can Balioglu
🚀 Big news for LLM researchers! #fairseq2 now has native support in #vLLM. Deploy your fine-tuned language models with vLLM in just one command for lightning-fast performance. Ready to accelerate your research like in FAIR? Check this out: facebookresearch.github.io/fairseq2/sta...
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facebookresearch.github.io
February 19, 2025 at 9:19 AM
🚀 Big news for LLM researchers! #fairseq2 now has native support in #vLLM. Deploy your fine-tuned language models with vLLM in just one command for lightning-fast performance. Ready to accelerate your research like in FAIR? Check this out: facebookresearch.github.io/fairseq2/sta...
Reposted by Can Balioglu
🖼️ A gallery of open-source projects and papers powered by #fairseq2! 🚀
Seamless Communication and Large Concept Models are 2 vivid examples that showcase the potential of what we are building.
More exciting FAIR research built on fairseq2 is on the way!
Seamless Communication and Large Concept Models are 2 vivid examples that showcase the potential of what we are building.
More exciting FAIR research built on fairseq2 is on the way!
February 14, 2025 at 10:18 AM
🖼️ A gallery of open-source projects and papers powered by #fairseq2! 🚀
Seamless Communication and Large Concept Models are 2 vivid examples that showcase the potential of what we are building.
More exciting FAIR research built on fairseq2 is on the way!
Seamless Communication and Large Concept Models are 2 vivid examples that showcase the potential of what we are building.
More exciting FAIR research built on fairseq2 is on the way!
Excited to announce our first "true" release of fairseq2! In v0.4, our main focus has been language model finetuning, preference optimization for scales up to 70B. These recipes are already widely used by many FAIR researchers and can easily be extended with new loss algorithms.
👋 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.
February 12, 2025 at 12:57 PM
Excited to announce our first "true" release of fairseq2! In v0.4, our main focus has been language model finetuning, preference optimization for scales up to 70B. These recipes are already widely used by many FAIR researchers and can easily be extended with new loss algorithms.