Now you can run any GGUF model from Hugging Face Hub with Ollama
OPEN SOURCE
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Differentiable Adaptive Merging: Faster Automated Model Fusion
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Differentiable Adaptive Merging I participated in a paper with @arcee_ai about a new automated merging technique (no manual parameter tuning!) Compared to other algorithms, like Evolutionary Merging, it is significantly faster to run and achieves the same level of performance.
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OSS Team Working on Fix Implementation Soon
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yes – oss team is at work on this right now – expect a fix soon
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H2O AI Partners with AI Verify Foundation for Responsible AI Testing
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We’re partnering with the AI Verify Foundation to advance responsible AI adoption in Singapore! We’re contributing benchmarks and code to AI Verify’s open-source Project #Moonshot toolkit for LLM application testing – https://
h2o.ai/blog/2024/h2o-
ai-collaboration-with-ai-verify-foundation/
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New Model Beats Llama-405B and All Open Source Competitors
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Thank you. Please note we beat every open source model, including Llama-405B.
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Model Merging Community Innovation and Creative Naming Trends
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The best part about model merging is how people build upon your models and come up with crazy names.
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Open Source Tools for Large Language Models
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Open Source LLM Tools https://
bit.ly/3N8Lwfm
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Building AI Code Assistant with SambaNova Cloud
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In this blog, we demonstrate how to build a useful application to power @continuedev
, the leading #OpenSource AI code assistant. With SambaNova Cloud, you can build custom autocomplete & chat experiences within VS Code or JetBrains. Learn more https://
sambanova.ai/blog/accelerat
ing-coding-with-sambanova-cloud
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OSS Canvas UX Alternative with Memory for User Preferences
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OSS version of OpenAI's Canvas UX… but also adds in memory (so if you make corrections/changes, it will remember your preferences for the future) s/o @BraceSproul for this!!
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Summary of paper using Llama 3.2
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Summary of paper using Llama 3.2 pic.twitter.com/9xsNnPlnnz
— AK (@_akhaliq) 15 octobre 2024Summary of paper using Llama 3.2