i foresee a new industry on Fiverr adding prompt injections to people's CVs. The future is hilarious, if you don't mind a bit of chaos.
nomadicsynth PRO
nomadicsynth
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Interesting. Did you learn how the creator of the dataset synthesised it?
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10 days? Rookie numbers 😊. so many side-quests. no idea what to do with myself lol. i'd love to hear about your ideas, and happy to give some feedback (for what it's worth)
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Hi everyone,
I've seen some unsuccessful attempts at running Wan2GP inside a Hugging Face Space, which is a shame as it is a great Gradio app!
So here is a fork that you can use, with some instructions on how to do this:
jbilcke-hf/Wan2GP_you_must_clone_this_space_to_use_it#1
Note : some things like persistent models/storage/custom LoRAs might not be fully working out of the box. If you need those, you might have to dig into the Wan2GP codebase, see how to tweak the storage folder. Happy hacking!
I've seen some unsuccessful attempts at running Wan2GP inside a Hugging Face Space, which is a shame as it is a great Gradio app!
So here is a fork that you can use, with some instructions on how to do this:
jbilcke-hf/Wan2GP_you_must_clone_this_space_to_use_it#1
Note : some things like persistent models/storage/custom LoRAs might not be fully working out of the box. If you need those, you might have to dig into the Wan2GP codebase, see how to tweak the storage folder. Happy hacking!
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I just finished AI Engineering by Chip Huyen. Probably the best resource I’ve seen that covers the full AI stack. People wondering how to shift their careers toward AI might find this very useful.
I recently shared this list of resources I’ve been using to learn AI:
🔗 https://github.com/ArturoNereu/AI-Study-Group
I recently shared this list of resources I’ve been using to learn AI:
🔗 https://github.com/ArturoNereu/AI-Study-Group
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codelion's
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🧠 We just implemented Andrej Karpathy's "third paradigm" for LLM learning!
System Prompt Learning (SPL) enables LLMs to automatically learn problem-solving strategies from experience, rather than relying on static prompts.
🚀 How it works:
Your LLM builds a database of effective strategies, selects the best ones for each problem, and refines them over time based on success rates.
📊 Results across math benchmarks:
Arena Hard: 29% → 37.6% (+8.6%)
AIME24: 23.33% → 30% (+6.67%)
OptILLMBench: 61% → 65% (+4%)
The best part? All strategies are human-readable and the system gets progressively better at problem types you use frequently.
✨ Key benefits:
🔄 Cumulative learning over time
📖 Transparent, inspectable strategies
🔌 Works with any OpenAI-compatible API
⚡ Simple integration: just add "spl-" prefix to your model
Built as an open-source plugin in optillm. After 500 queries, our system developed 129 strategies and refined 97 of them!
This feels like a genuine step toward AI that learns from experience while staying completely interpretable.
🔗 GitHub: https://github.com/codelion/optillm/tree/main/optillm/plugins/spl
📖 Full article: https://huggingface.co/blog/codelion/system-prompt-learning
🐦 Original Karpathy tweet: https://x.com/karpathy/status/1921368644069765486
Have you experimented with advanced system prompting? What strategies would you want your LLM to learn?
System Prompt Learning (SPL) enables LLMs to automatically learn problem-solving strategies from experience, rather than relying on static prompts.
🚀 How it works:
Your LLM builds a database of effective strategies, selects the best ones for each problem, and refines them over time based on success rates.
📊 Results across math benchmarks:
Arena Hard: 29% → 37.6% (+8.6%)
AIME24: 23.33% → 30% (+6.67%)
OptILLMBench: 61% → 65% (+4%)
The best part? All strategies are human-readable and the system gets progressively better at problem types you use frequently.
✨ Key benefits:
🔄 Cumulative learning over time
📖 Transparent, inspectable strategies
🔌 Works with any OpenAI-compatible API
⚡ Simple integration: just add "spl-" prefix to your model
Built as an open-source plugin in optillm. After 500 queries, our system developed 129 strategies and refined 97 of them!
This feels like a genuine step toward AI that learns from experience while staying completely interpretable.
🔗 GitHub: https://github.com/codelion/optillm/tree/main/optillm/plugins/spl
📖 Full article: https://huggingface.co/blog/codelion/system-prompt-learning
🐦 Original Karpathy tweet: https://x.com/karpathy/status/1921368644069765486
Have you experimented with advanced system prompting? What strategies would you want your LLM to learn?