Ready to start working with our new lightweight and multimodal Llama 3.2 models? Here are a few new resources from Meta to help you get started.
LLMS
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Cohere Command R Models Now Available on GitHub Marketplace
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These models are also available on GitHub Marketplace. Check out the listings here: https://
github.com/marketplace/mo
dels/azureml-cohere/Cohere-command-r-08-2024/
… https://
github.com/marketplace/mo
dels/azureml-cohere/Cohere-command-r-plus-08-2024
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Cohere Command R Plus 08-2024 Now Available on Azure
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Command R 08-2024 and Command R+ 8-2024 are now live on Microsoft @Azure
. Experience significant enhancements in coding, math, reasoning, and structured data analysis for enterprise applications. Deploy the models directly from the Azure Marketplace: https://
aka.ms/azureai/landin
g/Cohere-command-r-plus-08-2024
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User expresses excitement for Perplexity’s new Files search feature
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I discovered Files search on Perplexity and now cannot wait for it to be released any longer
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LangGraph and LangSmith case study with leading AI company Replit
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It's awesome to partner with leading AI companies like Replit We learned a LOT about LangGraph/LangSmith from working with them, and so we wrote up a technical case study to share some of those learnings
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Transform PDF Earnings Reports into Interactive Dashboards with LLMs
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You can transform a simple PDF earnings report into an interactive dashboard!
— Abacus.AI (@abacusai) 27 septembre 2024
Play around with different LLMs to see which works but we found that LLama-400B and Sonnet 3.5 does this task the best. pic.twitter.com/DTgZdJUZstYou can transform a simple PDF earnings report into an interactive dashboard! Play around with different LLMs to see which works but we found that LLama-400B and Sonnet 3.5 does this task the best.
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API Integration Skills for Data Science and LLM Workflows
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One of the important skill for anyone entering in to #datascience is to learn how to interact with an API. While many #LLMs have capabilities to do critical tasks you just need to know how to integrate them in your workflow and evaluate.
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Fine-tuning Llama 3.2 Models Locally and in the Cloud
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Here's how you can easily fine-tune latest llama 3.2 (1b and 3b) locally and on cloud:
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Building Function Management System with AI Capabilities
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I’m starting with functions for managing functions (create, update, delete, find, etc), and just enough ai ones to create new ones (LLM call, embed, similarity search).