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Top 20 Jupyter Notebook language-model Projects
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generative-ai-for-beginners
21 Lessons, Get Started Building with Generative AI đź”— https://microsoft.github.io/generative-ai-for-beginners/
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While I appreciate the pictures, really at the end of the day all you have is a glossary and slightly more detailed arbitrary hand waving.
What specific architecture is used to build a basic model?
Why is that specific combination of basic building blocks used?
Why does it work when other similar ones don’t?
I generally approve of simplifications, but these LLM simplifications are too vague and broad to be useful or meaningful.
Here my challenge: take that article and write an LLM.
No?
How about an article on raytracing?
Why is building an LLM miles of explanation of concepts and nothing concrete you can actually build?
Where’s my “LLM in a weekend” that covers the theory and how to actually implement one?
The distinction between this and something like https://github.com/rasbt/LLMs-from-scratch is stark.
My hot take is, if you haven’t built one, you don’t actually understand how they work, you just have a kind of vague kind-of-heard of it understanding, which is not the same thing.
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I'm quite interested in repeng [0] (representztion engineering) for steerability of (so fzr transformer based) LLMs and was wondering if anyone had tried such methods on rwkv (or mamba for that matter). Maybe there are some low hanging fruits about it.
[0] https://github.com/vgel/repeng/issues
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Deepdive-llama3-from-scratch
Achieve the llama3 inference step-by-step, grasp the core concepts, master the process derivation, implement the code.
Project mention: DeepDive: In-Depth Decryption of LLMs Construction and Inference from Scratch | news.ycombinator.com | 2025-02-26 -
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language-planner
Official Code for "Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents"
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SaaSHub
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voice-assistant-whisper-chatgpt
This repository will guide you to create your own Smart Virtual Assistant like Google Assistant using Open AI's ChatGPT, Whisper. The entire solution is created using Python & Gradio.
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Local-LLM-Langchain
Load local LLMs effortlessly in a Jupyter notebook for testing purposes alongside Langchain or other agents. Contains Oobagooga and KoboldAI versions of the langchain notebooks with examples.
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Smarty-GPT
A wrapper of LLMs that biases its behaviour using prompts and contexts in a transparent manner to the end-users
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tf-transformers
State of the art faster Transformer with Tensorflow 2.0 ( NLP, Computer Vision, Audio ).
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artificial-self-AMLD-2020
Workshop material for the AMLD 2020 workshop on "Meet your Artificial Self: Generate text that sounds like you"
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reweight-gpt
Reweight GPT - a simple neural network using transformer architecture for next character prediction
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augmented-interpretable-models
Interpretable and efficient predictors using pre-trained language models. Scikit-learn compatible.
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ai_story_scale
The AI story scale (AISS): A human rating scale for texts written with generative language models.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Jupyter Notebook language-model discussion
Jupyter Notebook language-model related posts
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Nucleotide Transformer: building robust foundation models for human genomics
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Binarize Clip for Multimodal Applications
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Database of 16,000 Artists Used to Train Midjourney AI Goes Viral
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Stable LM 3B: Bringing Sustainable, High-Performance LMs to Smart Devices
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FreeWilly 1 and 2, two new open-access LLMs
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Example Code needed
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Is Nicholas Renotte a good guide for a person who knows nothing about ML?
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A note from our sponsor - CodeRabbit
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Index
What are some of the best open-source language-model projects in Jupyter Notebook? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | generative-ai-for-beginners | 75,266 |
| 2 | LLMs-from-scratch | 41,977 |
| 3 | StableLM | 15,834 |
| 4 | repeng | 558 |
| 5 | Deepdive-llama3-from-scratch | 550 |
| 6 | bert-sklearn | 298 |
| 7 | language-planner | 267 |
| 8 | voice-assistant-whisper-chatgpt | 247 |
| 9 | Local-LLM-Langchain | 212 |
| 10 | gpt-3-simple-tutorial | 182 |
| 11 | Smarty-GPT | 141 |
| 12 | kruk | 94 |
| 13 | tf-transformers | 85 |
| 14 | artificial-self-AMLD-2020 | 81 |
| 15 | minGPT-TF | 57 |
| 16 | reweight-gpt | 51 |
| 17 | augmented-interpretable-models | 40 |
| 18 | gptq_for_langchain | 40 |
| 19 | BLOOM-fine-tuning | 40 |
| 20 | ai_story_scale | 9 |
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