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Openai-cookbook Alternatives
Similar projects and alternatives to openai-cookbook
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diffusers
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
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prompts
A free and open-source curation of prompts for OpenAI's GPT-3/Codex, EleutherAI's GPT-j, AlephAlpha's World Model and other language models. (by semiosis)
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InfluxDB
Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Platform where developers build real-time applications for analytics, IoT and cloud-native services. Easy to start, it is available in the cloud or on-premises.
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codesearch
Semantic Code Search tool. Query your codebases using natural language (by rahuldan)
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SonarQube
Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.
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gpt_index
GPT Index is a project consisting of a set of data structures designed to make it easier to use large external knowledge bases with LLMs.
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Hacker News API
Documentation and Samples for the Official HN API
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chatgpt-playground
Trivial experimental chat playground for chatgpt without the official api
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
openai-cookbook reviews and mentions
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Ask HN: How are you building apps that use LLMs?
Iterating workflows such as the ones described here https://github.com/openai/openai-cookbook/blob/main/techniques_to_improve_reliability.md is a bit tedious with Jupyter.
I've been using https://natto.dev/ to try out different workflows side-by-side, but was curious to see what other HN users were up to.
I'm looking for environments (Jupyter, Natto) more so than libraries like https://github.com/hwchase17/langchain or https://github.com/jerryjliu/gpt_index.
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Ask HN: Is anyone building a question answering system using the HN corpus?
Today, if someone wants to know what the HN community knows/thinks about a topic, they can either:
A) Search past HN comments on hn.algolia.com, or
B) Post a new 'Ask HN'.
LLMs could provide a new way to find answers within a corpus. These have been described elsewhere, e.g.
- https://github.com/openai/openai-cookbook/blob/main/examples/Question_answering_using_embeddings.ipynb
- https://news.ycombinator.com/item?id=34477543
I keep expecting someone (maybe minimaxir or simonw?) to post a 'Show HN: Get your question answered by the collective wisdom of HN', but I no one has so far (unless I missed the submission?).
Is someone already working on this?
- Queensland will join New South Wales in banning access to ChatGPT in state schools, though artificial intelligence experts have questioned how effective such a strategy is.
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What ChatGPT and AI-Based Program Generation Mean for Future of Software
There’s evidence that it can already solve more difficult problems when given the right prompts and constraints.
https://github.com/openai/openai-cookbook/blob/main/techniqu...
- GPT-3: Techniques to improve reliability
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OpenAI starts testing ChatGPT premium
https://github.com/openai/openai-cookbook/blob/main/examples... would be something to look at too.
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Show HN: GPTDuck – Ask questions about any GitHub repo
Thanks for sharing this!
I found this guide/example from OpenAI which was pretty clear:
https://github.com/openai/openai-cookbook/blob/main/examples...
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GPT prompt directory
This is a good place to start https://github.com/openai/openai-cookbook
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Starting Sep first, GPT-3 is becoming 3X Cheaper
As someone who's used the models a fair bit (I work at OpenAI), I mentally sort applications into four buckets:
-generative use cases, where you give the model the kernel of an idea and then you curate its output (blog writing, code completion, etc.)
-extractive use cases, where you give the model some big piece of text, and then process it in some way (e.g., extract names and addresses, classify it, ask a question about the text)
-transformational use cases, where you need to fix/adjust a piece of text, or translate from one domain to another (e.g., sometimes I'll use GPT-3 for little tasks like copying and pasting a table from a presentation and then asking the model to translate it to markdown; saves me a visit to Google and finding some table generator website)
-comparisons, where you use embeddings to do search/clustering/recommendations over any set of strings (e.g., can combo nicely with the Q&A use case above, where you search over a knowledge base)
I started a repo here with some barebones examples of each: https://github.com/openai/openai-cookbook/
If you're looking for examples of commercial applications, OpenAI published two blog posts highlighting a few:
-GPT-3 use cases (2021): https://openai.com/blog/gpt-3-apps/
-Codex use cases (2022): https://openai.com/blog/codex-apps/
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Training GPT-3 on a set of documents so you can ask it questions
Thanks - that link broke for me but this worked: https://github.com/openai/openai-cookbook/blob/main/examples/Question_answering_using_embeddings.ipynb
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