I’m taking a micro service inspired approach where every function is small but can be used in other functions. Having a whole bunch of baseline functions to use helps with reliability of the code gen. Level 3 should allows you create and debug those lower level functions upfront
CODE
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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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ebook2audiobook XTTS GitHub Repository Project
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github: https://
github.com/DrewThomasson/
ebook2audiobookXTTS
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AI Programs Flag Grammar Errors for Language Learners
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"Provide explanations to help them understand their mistakes"? Maybe. Like I know how to write programs that, especially if you're talking about second language learners, can say, hey, look, it's like the sentence has an agreement error or something and you can like flag it. >>
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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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AutoTrain: Versatile Machine Learning Tool for 20+ Tasks
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All you need is AutoTrain: https://
github.com/huggingface/au
totrain-advanced
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Supports 20+ tasks. Model files are yours. Works locally or on cloud. -
AutoTrain Advanced Open-Sourced and Maintained
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yes. it got open-sourced and changed its name to autotrain advanced (aka autotrain). im maintaining it. happy to answer any questions/concerns 🙂 github repo:
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Hugging Face Spaces to GitHub Repository Cloning Tool
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Hugging Face Spaces to GitHub Repo Enter the details to clone a Hugging Face Spaces repository and push it to a new GitHub repository. https://
huggingface.co/spaces/akhaliq
/spaces-to-github
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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).
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Programming Every Example: AI-Powered Data Refinement Framework
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We introduce Programming Every Example (ProX), a novel framework that treats data refinement as a programming task, enabling models to refine corpora by generating and executing fine-grained operations, such as string normalization, for each individual example at scale.