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tatsu-lab/stanford_alpaca

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Code and documentation to train Stanford's Alpaca models, and generate the data.

14 mentions on Hacker News by 13 people: 1 story, 13 comments · first 2023-03-13 · latest 2023-04-19

Mentions per year 14 mentions · busiest year 2023 (14)
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  1. https://github.com/tatsu-lab/stanford_alpaca
    comment by dougmwne · 2023-04-19 · in StableLM: A new open-source language model
  2. Yes this is the point of Stanford Alpaca https://github.com/tatsu-lab/stanford_alpaca They used the larger and more expensive text-davinci-003 model to fine-tune the smaller and cheaper 7B LLaMA model.
    comment by ftxbro · 2023-03-29 · in Ask HN: Is it possible to use current gen AI models to train next gen ones?
  3. …is so cheap. Surely, they figured out a way to break down one big box into smaller ones. [0]: https://github.com/tatsu-lab/stanford_alpaca/blob/main/assets/parse_analysis.png
    comment by bob1029 · 2023-03-29 · in What we still don’t know about how A.I. is trained
  4. Thanks! - Training code is https://github.com/tatsu-lab/stanford_alpaca - Params were mostly default (as in stanford_alpaca README), except for: per_device_train_batch_size=1, per_device_eval_batch_size=1 - Fine-tuning dataset was based on…
    comment by sockeye · 2023-03-23 · in Show HN: Web demo of 13B Alpaca-LLaMA trained on improved Stanford dataset
  5. …repo has the training script. The readme has the torchrun command and arguments used for train.py. https://github.com/tatsu-lab/stanford_alpaca/blob/main/train...
    comment by gorbypark · 2023-03-22 · in Show HN: ChatLLaMA – A ChatGPT style chatbot for Facebook's LLaMA
  6. …based on your custom dataset. [0] - https://github.com/promptslab/Awesome-Prompt-Engineering [1] - https://github.com/tatsu-lab/stanford_alpaca
    comment by itake · 2023-03-19 · in Not by AI
  7. On their GitHub repo ( https://github.com/tatsu-lab/stanford_alpaca ) they've added a notice: " Note: Due to safety concerns raised by the community, we have decided to shut down the Alpaca live demo. Thank you to everyone who provided…
    comment by viininnk · 2023-03-17 · in Stanford Alpaca web demo suspended “until further notice”
  8. Training code: https://github.com/tatsu-lab/stanford_alpaca#fine-tuning
    comment by bookofjoe · 2023-03-17 · in LLaMA: Large Language Model Meta AI
  9. …a 2-3 hours and voila. See the Readme in their repo where it mentions the fine-tuning script[0] [0] https://github.com/tatsu-lab/stanford_alpaca
    comment by danielbln · 2023-03-17 · in Show HN: Alpaca.cpp – Run an Instruction-Tuned Chat-Style LLM on a MacBook
  10. …hard. $100 worth of compute time to run the fine-tuning, and the training data they used is here: https://github.com/tatsu-lab/stanford_alpaca/blob/main/alpac... That would have the same licensing problems that they have though: that…
    comment by simonw · 2023-03-15 · in LLaMa running at 5 tokens/second on a Pixel 6
  11. https://github.com/tatsu-lab/stanford_alpaca Tada! Literally runs on a raspberry pi (very slowly). GPT models are incredible but the future is somehow even more amazing than that. I suspect this will be the approach for legal / medical…
    comment by f0e4c2f7 · 2023-03-15 · in GPT-4
  12. …at this point perhaps except LLaMa Alpaca 7B EDIT: I accidentially typed Alpine, it's Alpaca. https://github.com/tatsu-lab/stanford_alpaca
    comment by fswd · 2023-03-14 · in GPT4 is up to 6 times more expensive than GPT3.5
  13. Here's a link that opens their training data (52,000 rows) in Datasette Lite: https://lite.datasette.io/?json=https://github.com/tatsu-lab... Means you can run SQL LIKE queries against it to try and get a feel for what's in there. This…
    comment by simonw · 2023-03-13 · in Alpaca: A strong open-source instruction-following model
  14. ▲ 98
    Stanford Alpaca: An Instruction-following LLaMA model
    story by vkhuc · 2023-03-13 · 2 comments