Huge thank you to the @NVIDIA team for everything you do to support the Llama ecosystem!
OPEN SOURCE
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Open Source AI Innovation and Flexibility
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This type of innovation and flexibility is what open source AI is about.
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Qwen2-VL Released: New Vision Language Model Available
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Qwen2-VL is out demo: https://
huggingface.co/spaces/Qwen/Qw
en2-VL
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collection: https://
huggingface.co/collections/Qw
en/qwen2-vl-66cee7455501d7126940800d
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Monopriors: Library for Monocular Depth and Surface Analysis
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Monopriors
— AK (@_akhaliq) 29 août 2024
github: https://t.co/OopMNFFudl
A library to easily get monocular priors such as scale-invariant depths, metric depths, or surface normals. Using Rerun viewer, Pixi and Gradio for easy use pic.twitter.com/1G4UNX7ZdeMonopriors github: https://
github.com/pablovela5620/
monoprior
… A library to easily get monocular priors such as scale-invariant depths, metric depths, or surface normals. Using Rerun viewer, Pixi and Gradio for easy use -
Open source research gaining academic citations without formal paper
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I think I’m at about 50! I never did a paper so they’re citing my blog post or GitHub repo.
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Llama Reaches 350M Downloads on Hugging Face Hub
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"Llama is approaching 350M downloads on Hugging Face More than 10x compared to this time last year"
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Llama Models Approaching 350M Downloads on Hugging Face
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Open source AI is the way forward and today we're sharing a snapshot of how that's going with the adoption and use of Llama models. Read the full update here https://
go.fb.me/e7odag A few highlights
• Llama is approaching 350M downloads on @HuggingFace
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Importance of Open Educational Materials for Machine Learning Newcomers
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One very important technical tool is good open introductory educational material: textbooks, lecture notes, videos. O/W it's very difficult for newcomers w/o connections to learn the basics. See eg the classic @shai_s_shwartz @shaibendavid5 book https://
cs.huji.ac.il/~shais/Underst
andingMachineLearning/
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OpenRouter sending Llama 3.1 instruct prompts
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It's OpenRouter — AFAIK it's just naively sending the base model the same prompt format used for Llama 3.1 instruct. Other than that, that's the whole dialog; no system prompt.
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Llama 3.1 base — AI categories and topics
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Also see my previous thread demonstrating Llama 3.1 base: