flan-alpaca
This repository contains code for extending the Stanford Alpaca synthetic instruction tuning to existing instruction-tuned models such as Flan-T5. (by declare-lab)
llama.cpp
LLM inference in C/C++ (by ggerganov)
| flan-alpaca | llama.cpp | |
|---|---|---|
| 5 | 782 | |
| 337 | 58,425 | |
| -0.3% | - | |
| 5.7 | 10.0 | |
| 11 months ago | 3 days ago | |
| Python | C++ | |
| Apache License 2.0 | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
flan-alpaca
Posts with mentions or reviews of flan-alpaca.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-23.
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Is it feasible to develop multiple specialised language models that are small in size and expertise-specific, which can be merged to achieve comparable results to those obtained from a single large language model?
If you have enough task or domain specific training data, the model size becomes less important. For example, you can take an instruction tuned smaller model like FlanT5 and fine tune for your specific case: https://github.com/declare-lab/flan-alpaca
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Best Instruct-Trained Alternative to Alpaca/Vicuna?
Hi, you can try Flan-Alpaca here which does not have such restrictions: https://github.com/declare-lab/flan-alpaca
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Cerebras-GPT: A Family of Open, Compute-Efficient, Large Language Models
I've been following open source LLMs for a while and at first glance this doesn't seem too powerful compared to other open models, Flan-Alpaca[0] is licensed under Apache 2.0, and it seems to perform much better. Although I'm not sure about the legalities about that licensing, since it's basically Flan-T5 fine-tuned using the Alpaca dataset (which is under a Non-Commercial license).
Nonetheless, it's exciting to see all these open models popping up, and I hope that a LLM equivalent to Stable Diffusion comes sooner than later.
[0]: https://github.com/declare-lab/flan-alpaca
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[D] What is the best open source chatbot AI to do transfer learning on?
Someone's already taking care of that - Flan-Alpaca
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[P] ChatLLaMA - A ChatGPT style chatbot for Facebook's LLaMA
I think this might be exactly what you're looking for https://github.com/declare-lab/flan-alpaca
llama.cpp
Posts with mentions or reviews of llama.cpp.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-05-07.
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IBM Granite: A Family of Open Foundation Models for Code Intelligence
if you can compile stuff, then looking at llama.cpp (what ollama uses) is also interesting: https://github.com/ggerganov/llama.cpp
the server is here: https://github.com/ggerganov/llama.cpp/tree/master/examples/...
And you can search for any GGUF on huggingface
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Ask HN: Affordable hardware for running local large language models?
Yes, Metal seems to allow a maximum of 1/2 of the RAM for one process, and 3/4 of the RAM allocated to the GPU overall. There’s a kernel hack to fix it, but that comes with the usual system integrity caveats. https://github.com/ggerganov/llama.cpp/discussions/2182
- Xmake: A modern C/C++ build tool
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Better and Faster Large Language Models via Multi-Token Prediction
For anyone interested in exploring this, llama.cpp has an example implementation here:
https://github.com/ggerganov/llama.cpp/tree/master/examples/...
- Llama.cpp Bfloat16 Support
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Fine-tune your first large language model (LLM) with LoRA, llama.cpp, and KitOps in 5 easy steps
Getting started with LLMs can be intimidating. In this tutorial we will show you how to fine-tune a large language model using LoRA, facilitated by tools like llama.cpp and KitOps.
- GGML Flash Attention support merged into llama.cpp
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Phi-3 Weights Released
well https://github.com/ggerganov/llama.cpp/issues/6849
- Lossless Acceleration of LLM via Adaptive N-Gram Parallel Decoding
- Llama.cpp Working on Support for Llama3