stanford_alpaca
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stanford_alpaca | Open-Assistant | |
---|---|---|
108 | 329 | |
28,761 | 36,622 | |
1.3% | 0.7% | |
2.0 | 9.1 | |
about 1 month ago | about 1 month ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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stanford_alpaca
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How Open is Generative AI? Part 2
Alpaca is an instruction-oriented LLM derived from LLaMA, enhanced by Stanford researchers with a dataset of 52,000 examples of following instructions, sourced from OpenAI’s InstructGPT through the self-instruct method. The extensive self-instruct dataset, details of data generation, and the model refinement code were publicly disclosed. This model complies with the licensing requirements of its base model. Due to the utilization of InstructGPT for data generation, it also adheres to OpenAI’s usage terms, which prohibit the creation of models competing with OpenAI. This illustrates how dataset restrictions can indirectly affect the resulting fine-tuned model.
- Ask HN: AI/ML papers to catch up with current state of AI?
- OpenAI board in discussions with Sam Altman to return as CEO
- Are there any AI like ChatGPT without content restrictions?
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Fine-tuning LLMs with LoRA: A Gentle Introduction
In this article, we're going to experiment with LoRA and fine-tune Llama Alpaca using commercial hardware.
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Creating a new Finetuned model
Most papers I did read showed at least a thousand, even 10000 at several cases, so I assumed that to be the trend in the case of Low rank adapter(PEFT) training.(source: [2305.14314] QLoRA: Efficient Finetuning of Quantized LLMs (arxiv.org) , Stanford CRFM (Alpaca) and the minimum being openchat/openchat · Hugging Face ; There are a lot more examples)
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Shock tick up for wage growth to 7.3% in blow for Bank of England
I'm not talking about OpenAI ChatGPT I'm talking about things ALPACA, and where did they train these models? Off the existing models for a fraction of a fraction of a fraction of the cost: https://crfm.stanford.edu/2023/03/13/alpaca.html
- Bye bye Bing
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The idea maze for AI startups (2015)
I think there's a new approach for “How do you get the data?” that wasn't available when this article was written in 2015. The new text and image generative models can now be used to synthesize training datasets.
I was working on an typing autocorrect project and needed a corpus of "text messages". Most of the traditional NLP corpuses like those available through NLTK [0] aren't suitable. But it was easy to script ChatGPT to generate thousands of believable text messages by throwing random topics at it.
Similarly, you can synthesize a training dataset by giving GPT the outputs/labels and asking it to generate a variety of inputs. For sentiment analysis... "Give me 1000 negative movie reviews" and "Now give me 1000 positive movie reviews".
The Alpaca folks used GPT-3 to generate high-quality instruction-following datasets [1] based on a small set of human samples.
Etc.
[0] https://www.nltk.org/nltk_data/
[1] https://crfm.stanford.edu/2023/03/13/alpaca.html
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Repos and tutorials for a full finetune (not LoRA)
AFAIK, the original alpaca repo was a full finetune. https://github.com/tatsu-lab/stanford_alpaca
Open-Assistant
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Best open source AI chatbot alternative?
For open assistant, the code: https://github.com/LAION-AI/Open-Assistant/tree/main/inference
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GPT-4 Turbo for free with no sign up, and most importantly no Bing
Is this being used to collect chat results for synthetic data and/or training like https://github.com/LAION-AI/Open-Assistant did? I believe they gave away GPT-4 api calls via a text interface and absorbed the cost to later build a dataset of chats.
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OpenAI now sends email threats?!
https://open-assistant.io seems to have the same guardrails, as ChatGPT. Tried it on several prompts and it wouldn't comply.
- ChatGPT-Antworten nach Schulnoten bewerten
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Chat GPT Alternatives?
Open-Assistant [https://open-assistant.io/]
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What are the best AI tools you've ACTUALLY used?
Open Assistant by LAION AI on GitHub
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Keep Artificial Intelligence Free, protect it from monopolies: please sign this petition
To add to this if you want something for free or at least close to free, contribute to OpenSource projects like https://open-assistant.io/
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If I had to get someone from total zero to ChatGPT power user
Also, there are fairly useful alternatives like GPT4ALL and Open Assistant that you can run locally.
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Compiling a Comprehensive List of Publicly Usable LLM Q&A Services - Need Your Input!
https://open-assistant.io - oasst-sft-6-llama-30b
- Proposal for a Crowd-Sourced AI Feedback System
What are some alternatives?
alpaca-lora - Instruct-tune LLaMA on consumer hardware
KoboldAI-Client
ChatGLM-6B - ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
llama.cpp - LLM inference in C/C++
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
llama - Inference code for Llama models
Alpaca-Turbo - Web UI to run alpaca model locally
gpt4all - gpt4all: run open-source LLMs anywhere
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/Auto-GPT]
llama_index - LlamaIndex is a data framework for your LLM applications