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Stanford_alpaca Alternatives
Similar projects and alternatives to stanford_alpaca
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textgen
Open-source desktop app for local LLMs. Text, vision, tool-calling, OpenAI/Anthropic-compatible API. 100% private.
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Open-Assistant
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
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transformers
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
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petals
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
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FastChat
An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
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character-editor
Discontinued Create, edit and convert AI character files for CharacterAI, Pygmalion, Text Generation, KoboldAI and TavernAI [GET https://api.github.com/repos/ZoltanAI/character-editor: 404 - Not Found // See: https://docs.github.com/rest]
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serge
A web interface for chatting with Alpaca through llama.cpp. Fully dockerized, with an easy to use API.
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better stanford_alpaca alternative or higher similarity.
stanford_alpaca discussion
stanford_alpaca reviews and mentions
Posts with mentions or reviews of stanford_alpaca.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-19.
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What is Alpaca LLM?
# Clone the Alpaca LLM repository git clone https://github.com/tatsu-lab/stanford_alpaca.git cd stanford_alpaca
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AI Engineer Reading List
I think most of the instruction fine-tuning methods for oss models stem from Alpaca, so it should be included: https://crfm.stanford.edu/2023/03/13/alpaca.html
And the one referenced in there on synthetic data generation: https://arxiv.org/abs/2212.10560
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5 AI Myths Debunked: Learn the Facts
The quality of the data and the training methodology are often more critical determinants of a model's performance and accuracy. This has already been proved with the Alpaca experiment by Stanford where a simple 7 billion features powered Llama-based LLM could tie the astonishing 176 billion features powered ChatGPT 3.5.
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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
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A note from our sponsor - SaaSHub
www.saashub.com | 13 Jun 2026
Stats
Basic stanford_alpaca repo stats
111
30,261
0.0
almost 2 years ago
tatsu-lab/stanford_alpaca is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of stanford_alpaca is Python.
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