Leverage the power of language models to build real-world applications with @hemanham at the Future of Data & AI virtual conference organized by @DataScienceDojo 2 Mar, Thur
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LLMS
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Language Models for Real-World Applications at Future of Data AI
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Meta Announces LLaMA LLM Following Blender Bot 3 Release
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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.
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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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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://
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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.
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LLaMA-65B Outperforms Chinchilla and PaLM on Reasoning Benchmarks
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On Common Sense Reasoning, Closed-book Question Answering, and Reading Comprehension, LLaMA-65B outperforms Chinchilla 70B and PaLM 540B on almost all benchmarks.
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LLaMA-65B Outperforms Minerva-62B on GSM8k Without Mathematical Fine-tuning
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LLaMA-65B outperforms Minerva-62B on GSM8k, even though it has not been fine-tuned on any mathematical dataset. On the MATH benchmark, it outperforms PaLM-62B (but is quite below Minerva-62B)
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