StanfordQuadruped
prompt-engineering
| StanfordQuadruped | prompt-engineering | |
|---|---|---|
| 3 | 18 | |
| 1,433 | 8,028 | |
| 1.0% | 2.8% | |
| 0.0 | 5.1 | |
| 30 days ago | 7 months ago | |
| Python | ||
| MIT License | MIT License |
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StanfordQuadruped
- FLaNK Stack Weekly for 20 June 2023
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Trying to make Sandford Pupper v1
I just pulled up the cad. The robot is open source so there is a good amount of documentation. The leg design is the same as most quadruped robots use 3 revolute joints. While the pupper does have a 4 bar linkage for the knee, I'm fairly certain that the link lengths mean its just a parallelogram. This leg design is simple enough that your unlikely to find a research paper covering it. Here is the code where they do the kinematics: https://github.com/stanfordroboticsclub/StanfordQuadruped/blob/master/pupper/Kinematics.py
- First robotics project (Quadraped) how to start?
prompt-engineering
- Ask HN: Any good collection of writing prompts for GPT 3.5/4?
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Show HN: LLM Agent Paper List
An agent is a style of prompt that lets LLMs act as reasoning engines. It's also known as the ReAct pattern (which engineers are avoiding using for namespace collision reasions).
You can read a good intro example here: https://github.com/brexhq/prompt-engineering#react
- FLaNK Stack Weekly for 20 June 2023
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What are your long-term career goals?
Well, if developers get replaced by AI, then who are the managers going to manage :). I personally don't think AI is just going to replace us. The way we work will continue to change as new AI tools come out. I'm taking time to tinker with new tools and seeing how others do as well (e.g., I found Brex's tips and tricks for working with LLMs very insightful: https://github.com/brexhq/prompt-engineering).
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A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT
I recognize there's plenty of catnip here when it comes to calling this "engineering" or not, however, whatever you want to call it (prompt fiddling?), the techniques are crucial if you want to achieve reasonably consistent output from current-state LLMs. As models improve concerns about context window limitations will be reduced and it will be easier to discern user intent.
These are good straight-to-the-point guides:
- Prompt Engineering by BrexHQ: https://github.com/brexhq/prompt-engineering
- OpenAI guidance: https://help.openai.com/en/articles/6654000-best-practices-f...
- https://devblogs.microsoft.com/dotnet/gpt-prompt-engineering...
- (great examples): https://www.deeplearning.ai/short-courses/chatgpt-prompt-eng...
tl;dr:
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(2/2) May 2023
Brex's Prompt Engineering Guide (https://github.com/brexhq/prompt-engineering)
- GitHub - brexhq/prompt-engineering: Tips and tricks for working with Large Language Models like OpenAI's GPT-4.
- Brex’s Prompt Engineering Guide
What are some alternatives?
gpt-engineer - Specify what you want it to build, the AI asks for clarification, and then builds it.
promptfoo - Test your prompts, models, and RAGs. Catch regressions and improve prompt quality. LLM evals for OpenAI, Azure, Anthropic, Gemini, Mistral, Llama, Bedrock, Ollama, and other local & private models with CI/CD integration.
FinGPT - FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
Prompt-Engineering-Guide - 🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
keep - The open-source alert management and AIOps platform
ali-dbhub - 已迁移新仓库，此版本将不再维护
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%
fastjson2 - 🚄 FASTJSON2 is a Java JSON library with excellent performance.
chathub - All-in-one chatbot client
jsoup - jsoup: the Java HTML parser, built for HTML editing, cleaning, scraping, and XSS safety.
canal - 阿里巴巴 MySQL binlog 增量订阅&消费组件