alpaca-electron
mlc-llm
| alpaca-electron | mlc-llm | |
|---|---|---|
| 8 | 89 | |
| 1,261 | 17,150 | |
| - | 4.3% | |
| 5.9 | 9.9 | |
| about 1 month ago | 5 days ago | |
| JavaScript | Python | |
| MIT License | Apache License 2.0 |
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.
alpaca-electron
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Are you sure you are focusing on the right things? (venting)
I sympathize. There are some efforts here and there but it's not something that resonates with the enthusiast crowd much. An abandoned example here: ItsPi3141/alpaca-electron
- Guess I am kinda famous now
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one-click install LLM desktop apps
Look up troublechute on youtube. Or alpaca electron
- What's the most basic NVIDIA graphics card that will work with mainstream 7B GPU models?
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Locally Hosted ChatGPT3 or Higher
I recently tried alpaca electron with the 7b model. I am surprised how well this runs on my own hardware with very little CPU and RAM consumption.
- Running oobabooga with Alpaca on Apple Silicon (M1/M2)
- Optimization Of Computational Power & Data Transfer For Elly (Global AI)
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Cerebras-GPT: A Family of Open, Compute-Efficient, Large Language Models
Here's alpaca running in electron. Not exactly one click but close.
https://github.com/ItsPi3141/alpaca-electron
mlc-llm
- FLaNK 04 March 2024
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Ai on a android phone?
This one uses gpu, it doesn't support Mistral yet: https://github.com/mlc-ai/mlc-llm
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MLC vs llama.cpp
I have tried running mistral 7B with MLC on my m1 metal. And it kept crushing (git issue with description). Memory inefficiency problems.
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[Project] Scaling LLama2 70B with Multi NVIDIA and AMD GPUs under 3k budget
Project: https://github.com/mlc-ai/mlc-llm
- Scaling LLama2-70B with Multi Nvidia/AMD GPU
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AMD May Get Across the CUDA Moat
For LLM inference, a shoutout to MLC LLM, which runs LLM models on basically any API that's widely available: https://github.com/mlc-ai/mlc-llm
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ROCm Is AMD's #1 Priority, Executive Says
One of your problems might be that gfx1032 is not supported by AMD's ROCm packages, which has a laughably short list of supported hardware: https://rocm.docs.amd.com/en/latest/release/gpu_os_support.h...
The normal workaround is to assign the closest architecture, eg gfx1030, so `HSA_OVERRIDE_GFX_VERSION=10.3.0` might help
Also, it looks like some of your tested projects are OpenCL? For me, I do something like: `yay -S rocm-hip-sdk rocm-ml-sdk rocm-opencl-sdk` to cover all the bases.
My recent interest has been LLMs and this is my general step by step for those (llama.cpp, exllama) for those interested: https://llm-tracker.info/books/howto-guides/page/amd-gpus
I didn't port the docs back in, but also here's a step-by-step w/ my adventures getting TVM/MLC working w/ an APU: https://github.com/mlc-ai/mlc-llm/issues/787
From my experience, ROCm is improving, but there's a good reason that Nvidia has 90% market share even at big price premiums.
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Show HN: Ollama for Linux – Run LLMs on Linux with GPU Acceleration
Maybe they're talking about https://github.com/mlc-ai/mlc-llm which is used for web-llm (https://github.com/mlc-ai/web-llm)? Seems to be using TVM.
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Show HN: Fine-tune your own Llama 2 to replace GPT-3.5/4
you already have TVM for the cross platform stuff
see https://tvm.apache.org/docs/how_to/deploy/android.html
or https://octoml.ai/blog/using-swift-and-apache-tvm-to-develop...
or https://github.com/mlc-ai/mlc-llm
- Ask HN: Are you training and running custom LLMs and how are you doing it?
What are some alternatives?
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++
stable-diffusion-ui - Easiest 1-click way to install and use Stable Diffusion on your computer. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the generated image. [Moved to: https://github.com/easydiffusion/easydiffusion]
ggml - Tensor library for machine learning
codealpaca
tvm - Open deep learning compiler stack for cpu, gpu and specialized accelerators
catai - Run AI ✨ assistant locally! with simple API for Node.js 🚀
flan-alpaca - This repository contains code for extending the Stanford Alpaca synthetic instruction tuning to existing instruction-tuned models such as Flan-T5.
llama-cpp-python - Python bindings for llama.cpp
dalai - The simplest way to run LLaMA on your local machine
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.