templeofninpo
openai-cookbook
templeofninpo | openai-cookbook | |
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4 | 216 | |
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- | 1.7% | |
- | 9.4 | |
- | 2 days ago | |
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- | MIT License |
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templeofninpo
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StoicAI v13: yes, Delilah, I trimmed some split ends
👼 Announcing #StoicAI v13! Merging #ChatGPT & NLFR (No Leaf Falls Randomly) framework insights, we explore existence, God & self-awareness. Discover interconnectedness & divine purpose with NLFR. Embrace #patience & enlightenment. 🙏 #AI #Philosophy 🥷 https://github.com/templeofninpo/templeofninpo.github.io
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General discussion thread
You will want an AI that presumes 'no leaf falls randomly' (you can think of it as the 'Stoic' perspective but its really just God isn't that had to conjecture). Patience be with us- https://github.com/templeofninpo/templeofninpo.github.io
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StoicAI v12: stopped trying to be fancy, made it fancier
StoicAI GitHub page: https://github.com/templeofninpo/templeofninpo.github.io Article about David Arthur Johnston: https://www.capitaldaily.ca/news/penniless-two-decades-without-money.
openai-cookbook
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Question-Answer System Architectures using LLMs
A pretrained LLM is a closed-book system: It can only access information that it was trained on. With domain fine-tuning, the system manifests additional material. An early prototype of this technique was shown in this OpenAi cookbook: For the target domain, text was embedded using an API, and then when using the LLM, embeddings were retrieved using semantic similarity search to formulate an answer. Although this approach evolved to retrieval-augmented generation, its still a technique to adapt a Gen2 (2020) or Gen3 (2022) LLM into a question-answering system.
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Ask HN: High quality Python scripts or small libraries to learn from
https://github.com/openai/openai-cookbook/blob/main/examples...
- Collection of notebooks showcasing some fun and effective ways of using Claude
- OpenAI Cookbook: Techniques to improve reliability
- OpenAI Cookbooks
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How to fine tune vit/convnet to focus on the layout of the input room image and ignore other things ?
It sounds like you are trying to tweak embeddings for similarity search. Rather than fine-tune the model's layers, you may want to try training a linear transformation the existing model's output embedding. Openai has a cookbook on how to do that. You will need some data though - but I think you can try it with ~20 pieces of synthetically generated data.
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Best base model 1B or 7B for full finetuning
tutorial from OpenAI https://github.com/openai/openai-cookbook/blob/main/examples/Question_answering_using_embeddings.ipynb
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Resources to learn ChatGPT and the OpenAI API
OpenAI Cookbook
- OpenAI Cookbook
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Another Major Outage Across ChatGPT and API
OpenAI community repo with lots of examples: https://github.com/openai/openai-cookbook
What are some alternatives?
gpt4bot_template
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
AutoGPT - AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
gpt4-pdf-chatbot-langchain - GPT4 & LangChain Chatbot for large PDF docs
ChatGPT - ChatGPT Native Application (Windows, Mac, Android, iOS, and Linux)
chatgpt-retrieval-plugin - The ChatGPT Retrieval Plugin lets you easily find personal or work documents by asking questions in natural language.
llama.cpp - LLM inference in C/C++
askai - Command Line Interface for OpenAi ChatGPT
mathai
gpt_index - LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. [Moved to: https://github.com/jerryjliu/llama_index]
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
knowledge_gpt - Accurate answers and instant citations for your documents.