So excited to see more biology open-source models! Chai by @chaidiscovery does structure predictions at AlphaFold3 levels of accuracy and able to handle multi-peptide or peptide-ligand complexes rather than just single chains. All in Apache 2.0 on Hugging Face:
OPEN SOURCE
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FLUX LoRAs Community Reaches 10000 Models Milestone
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Congratulations to the @bfl_ml community for 10,000+ FLUX LoRAs
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AI2 Presents OLMo 2, New Open Source LLMs Family
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[#Article] LLMs Research: AI2 Presents OLMo 2, Its Latest Completely Open Source LLMs Family https://actuia.com/actualite/recherche-sur-les-llms-ai2-presente-olmo-2-sa-derniere-famille-de-llms-totalement-open-source/
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#AI #artificialintelligence -
Cognify: Automated Gen-AI Workflow Optimization Tool
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introducing Cognify: Automated, Multi-Faceted Gen-AI Workflow Optimization https://
github.com/GenseeAI/cogni
fy
… a tool that automatically enhances generation quality and reduces costs for gen-AI workflows, including those written with LangChain, DSPy, and annotated Python. -
GraphCast: DeepMind’s Open-Source AI Weather Forecasting Model
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Check out the codebase here: https://
github.com/google-deepmin
d/graphcast
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DeepMind Open Sources GenCast Weather Forecasting Model
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DeepMind is on fire today, fully open sourced GenCast – SOTA diffusion based weather forecasting (ensemble) model! can predict temperature 15 days ahead in just 8 minutes powered by TPU v5e Code and weights open source! (although in a google cloud bucket)
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HellaSwag Evaluation Script for Language Models Released
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You can also find a HellaSwag evaluation script that works with one large batch item, EOT separators, and document_mask here: https://
github.com/alexjc/nanogpt
-speedrun/blob/master/eval_gpt2.py
… It's setup to use TokenMonster too, so you can check the scores on downstream benchmarks easily hopefully. -
Model weights release on Hugging Face platform
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Congrats on the release! Would be nice to have the weights on http://
hf.co happy to help with that! cc: @cyrilzakka too -
TokenMonster vocabulary files released for AI models
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I also uploaded the binary files for the tokens to this repository, which you can use as drop-in replacement. The TokenMonster vocabulary file is alongside the tokens and on GitHub too: