Following the insanity of Blender Bot 3 last year, Meta will be releasing a new LLM called LLaMA. Also, brilliant move to have these announcements roll out through Zuck’s broadcast channel to market two products at once.
OPEN SOURCE
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Hugging Face Inference Endpoints Reaches 1000 Paying Customers
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We just crossed 1,000 paying customers for our inference endpoints (easily deploy any open-source ML models), including @mantisnlp who were kind enough to write why and how they use it. Congrats to @_philschmid and team! https://
medium.com/mantisnlp/why-
were-switching-to-hugging-face-inference-endpoints-and-maybe-you-should-too-829371dcd330
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Open Science and Efficient AI Models on Hugging Face
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Open science and open source can't stop won't stop! + smaller more efficient models for the win! Soon on @huggingface
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Open-source initiatives democratizing generative AI in 2023
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This feeds into one of the key trends I predicted for 2023: the evolution of open-source initiatives to democratise (Gen) AI.
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AWS and Hugging Face collaboration prevents AI monopolies
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I’ve contemplated a future where a few well-resourced actors own and control powerful AI systems – and I have to say, this doesn't necessarily strike me as a good idea. Collabs like this between AWS and @huggingface are going help prevent AI monopolies.
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Hugging Face AWS collaboration makes generative models widely accessible
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Why the @huggingface / @awscloud collab is a bid deal: Hugging Face is on a mission to make the best generative models (which require a lot of data, computing power and basically $$$$$) widely accessible.
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Meta Releases LLaMA Foundational Language Model Publicly
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Today we're publicly releasing LLaMA, a state-of-the-art foundational LLM, as part of our ongoing commitment to open science, transparency and democratized access to new research. Learn more & request access https://
bit.ly/3SoXdQE -
LLaMA: Competitive AI Model That’s Smaller and More Efficient
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LLaMA (Large Language Model Meta AI) achieves results competitive with the best currently released models while being smaller & more efficient — increasing accessibility to this technology for more researchers working on this important subfield of AI across the globe.
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Instruction Finetuning Results: LLaMA-I Outperforms Flan-PaLM
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We also briefly tried instruction finetuning using the approach of Chung et al. (2022).
The resulting model, LLaMA-I, outperforms Flan-PaLM-cont (62B) on MMLU and showcases some interesting instruct capabilities.
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LLaMA-62B Surpasses PaLM on Code Generation Benchmarks
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On code generation benchmarks, LLaMA-62B outperforms cont-PaLM (62B) as well as PaLM-540B.