Neurite
openai-cookbook
| Neurite | openai-cookbook | |
|---|---|---|
| 47 | 215 | |
| 768 | 56,065 | |
| - | 1.0% | |
| 9.2 | 9.5 | |
| 5 days ago | 2 days ago | |
| JavaScript | MDX | |
| MIT License | MIT License |
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Neurite
- Q* Could Be It - Forget AlphaGO - It's Diplomacy - Peg 1 May Have Fallen - Noam Brown May Have Achieved The Improbable - Is this Q* Leak 2.0?
- Node interface physics simulated within a fractal
- Tuesday Self-Promotion Thread
- Neurite has seen some significant improvements. Will be creating more video documentation soon.
- Neurite has seen some significant improvements. Will be creating new video documentation soon
- Neurite has seen some significant improvements. Will be creating new video documentation soon.
- Looking for open-source projects to contribute to
- How to include mindmaps into notes?
- Do you think we will be able to create our "own internet" in the future? By that I mean, simulating sites like reddit populated with AIs reacting to our content.
- How to make ChatGPT remember previous logs?
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?
tree-of-thought-llm - [NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
tree-of-thoughts - Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%
gpt4-pdf-chatbot-langchain - GPT4 & LangChain Chatbot for large PDF docs
zep - Zep: Long-Term Memory for AI Assistants.
chatgpt-retrieval-plugin - The ChatGPT Retrieval Plugin lets you easily find personal or work documents by asking questions in natural language.
AgentGPT - 🤖 Assemble, configure, and deploy autonomous AI Agents in your browser.
askai - Command Line Interface for OpenAi ChatGPT
auto-gpt-web - Set Your Goals, AI Achieves Them.
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]
loxilb - eBPF based cloud-native load-balancer. Powering Kubernetes|Edge|5G|IoT|XaaS Apps.
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows