one-click-installers
dalai
one-click-installers | dalai | |
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18 | 59 | |
470 | 13,060 | |
- | - | |
8.9 | 6.5 | |
8 months ago | 5 months ago | |
Python | CSS | |
GNU Affero General Public License v3.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
one-click-installers
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amd gpus on windows support?
AMD does not offer installation options for ROCm on Windows. I'm not familiar with the workarounds to make it work; if you find a solution, you can contribute it to https://github.com/oobabooga/one-click-installers/
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Oobabooga for Windows
Running start_windows.bat should take care of everything.
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Quant-Cude Error?
Had the same issue, turns out I was using an old 1 click installer / updater, you need to use https://github.com/oobabooga/one-click-installers and reinstall everything from scratch
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Cant find the "start: file.
Are you sure you're looking at the right folder? start_windows.bat is there. It's listed in the source code: https://github.com/oobabooga/one-click-installers
- Any UI that allows Windows + AMD GPU ?
- WizardLM-30B-Uncensored
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13b-4bit-128g - Trying to run compressed model without success. ( problem exist only with 13b models for some reason ) No error code has been displayed.
one-click-installers/INSTRUCTIONS.TXT
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GPT4All: A little helper to get started
https://github.com/oobabooga/one-click-installers/issues/56 they explain it over here.
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Visual Studio compile errors
I solved this by adding the Individual components 2019 Windows 10 SDK, C++ CMake tools for Windows, and MSVC v142 - VS 2019 C++ build tools. See https://github.com/oobabooga/one-click-installers/issues/56
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python setup.py bdist_wheel did not run successfully.
It appears one of the extensions isn't pre-compiled on install. I believe you have the same problem as listed here. https://github.com/oobabooga/one-click-installers/issues/56
dalai
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Ask HN: What are the capabilities of consumer grade hardware to work with LLMs?
I agree, I've definitely seen way more information about running image synthesis models like Stable Diffusion locally than I have LLMs. It's counterintuitive to me that Stable Diffusion takes less RAM than an LLM, especially considering it still needs the word vectors. Goes to show I know nothing.
I guess it comes down to the requirement of a very high end (or multiple) GPU that makes it impractical for most vs just running it in Colab or something.
Tho there are some efforts:
https://github.com/cocktailpeanut/dalai
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Meta to release open-source commercial AI model
If you're just looking to play with something locally for the first time, this is the simplest project I've found and has a simple web UI: https://github.com/cocktailpeanut/dalai
It works for 7B/13B/30B/65B LLaMA and Alpaca (fine-tuned LLaMA which definitely works better). The smaller models at least should run on pretty much any computer.
- How can I run a large language model locally?
- meirl
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FreedomGPT: AI with no censorship
I am not against easy mode options dude, for example I used to run GANs through command line. I replaced them with Upscayl when I found it. Convenience is king after all. Something about this one isn't right though. They are advertising it as a model they built meanwhile their own github show it to be a frontend of LLAMA. Why aren't they honest about it? Why use bots to spam about it? This causes me to not trust the executable they share to 1 to 1 compliation of the source code neither. I would still recommend looking for more decent alternatives. Btw, running it directly isn't that complicated
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Google removes the waitlist on Bard today and will be available in 180 more countries
https://github.com/ggerganov/llama.cpp https://github.com/oobabooga/text-generation-webui https://github.com/mlc-ai/mlc-llm https://github.com/cocktailpeanut/dalai https://github.com/ido-pluto/catai (this is super easy to install but it doesnt provide an api or have integration with langchain)
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ChatGPT Data Breach BreakDown - Why it Should be a Concern for Everyone!
This was easy to get running: https://github.com/cocktailpeanut/dalai with alpaca 13B (on my 16GB or ram)
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A brief history of LLaMA models
I had it running before with Dalai (https://github.com/cocktailpeanut/dalai) but have since moved to using the browser based WebGPU method (https://mlc.ai/web-llm/) which uses Vicuna 7B and is quite good.
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Meet Atom the GPT Assistant, an AI-powered Smart Home Assistant. It's like Google Assistant but with endless possibility of ChatGPT, it's like Siri but with extensibility of Open Source power.
https://github.com/nsarrazin/serge let's you pick which model and runs in a container. For API https://github.com/cocktailpeanut/dalai looks super promising.
- Mercredi Tech - 2023-04-26
What are some alternatives?
GPTQ-for-LLaMa - 4 bits quantization of LLaMa using GPTQ
gpt4all - gpt4all: run open-source LLMs anywhere
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
gradio - Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
llama - Inference code for Llama models
KoboldAI
alpaca-lora - Instruct-tune LLaMA on consumer hardware
WizardVicunaLM - LLM that combines the principles of wizardLM and vicunaLM
llama.cpp - LLM inference in C/C++
micromamba-releases - Micromamba executables mirrored from conda-forge as Github releases
FastChat - An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.