pyllama
alpaca.cpp
pyllama | alpaca.cpp | |
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5 | 94 | |
2,789 | 9,878 | |
- | - | |
5.0 | 9.4 | |
6 months ago | about 1 year ago | |
Python | C | |
GNU General Public License v3.0 only | MIT License |
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pyllama
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Tech pioneers call for six-month pause of "out-of-control" AI development
Got u fam
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Alpaca 7B Training - $75/Hour --> Bay Area? [P]
I am the author of pyllama https://github.com/juncongmoo/pyllama
- Integrate LLaMA into python code
- Together Releases The First Open-Source ChatGPT Alternative Called OpenChatKit
- pyllama - I just published a python library for LLaMA with Single GPU inference code
alpaca.cpp
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LLaMA Now Goes Faster on CPUs
Where's the 30B-in-6GB claim? ^FGB in your GH link finds [0] which is neither by jart nor by ggerganov but by another user who promptly gets told to look at [1] where Justine denies that claim.
[0] https://github.com/antimatter15/alpaca.cpp/issues/182
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Is there potential to short NVDA?
You can just download the language model, dude!!! Everyone doesn’t need to make their own and the open source models literally get better every day.
- [Oobabooga] Alpaca.cpp est extrêmement simple à travailler.
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Hollywood’s Screenwriters Are Right to Fear AI
Alpaca
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Square Enix’s AI Tech Demo Is a Staggering Failure
Square could have also trained a more specific data source for their NLP, very similar to Alpaca. Alpaca was trained from interactions from a larger dataset. So while it isn't as smart, it's still able to understand instructions and act upon them.
- [Singularity] Ich bin Alpaka 13B - Frag mich alles
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Alpaca Vs. Final Jeopardy
The model I found was in 8 parts. The alpaca.cpp chat client (chat.cpp) needs to be modified to run the 8 part model, documented here: https://github.com/antimatter15/alpaca.cpp/issues/149
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LocalAI: OpenAI compatible API to run LLM models locally on consumer grade hardware!
try the instructions on this github repo https://github.com/antimatter15/alpaca.cpp, its not the best one but I was able to run this model on my linux machine with 16GB memory, I think its a good starting point.
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What educational materials do you think would be most useful during/after collapse?
Doesn't run offline. If you're running something without a beefy-ish GPU, there's https://github.com/antimatter15/alpaca.cpp .
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ChatGPT Reignited My Passion For Coding
Ye, atm. toying with alpaca 7B/13B in a local install.
What are some alternatives?
playground - Play with neural networks!
gpt4all - gpt4all: run open-source LLMs anywhere
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
llama.cpp - LLM inference in C/C++
clip-interrogator - Image to prompt with BLIP and CLIP
coral-pi-rest-server - Perform inferencing of tensorflow-lite models on an RPi with acceleration from Coral USB stick
tortoise-tts-fast - Fast TorToiSe inference (5x or your money back!)
ggml - Tensor library for machine learning
llm - An ecosystem of Rust libraries for working with large language models
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
alpaca-lora - Instruct-tune LLaMA on consumer hardware