brev-cli
mlc-llm
| brev-cli | mlc-llm | |
|---|---|---|
| 7 | 89 | |
| 198 | 17,215 | |
| 1.5% | 4.6% | |
| 7.9 | 9.9 | |
| 5 days ago | 4 days ago | |
| Go | Python | |
| MIT License | Apache License 2.0 |
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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.
brev-cli
- Brev: Start fine-tuning and training models in < 10 minutes
- OpenLLaMA: An Open Reproduction of LLaMA
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Using the cloud or buying a GPU
I don't have a PC right now that will run StableDiffusion. I can build one but I think I'm going to need a pretty powerful GPU which I'm not sure I can afford right now. I started using something called Brev https://brev.dev/ (no, I don't work there just found it searching). It's pretty affordable and super easy to setup.
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is there a good guide on how to train an ai to simulate your own art work?
I just finished listening to an episode of the Practical AI podcast, where they talked with Nader Khalil from brev.dev. They talked a little bit about setting up dreambooth and training it with ten images in about 4 minutes. I havent tested it, but it is worth a try. Brev.dev is a way to set up virtual machines and developement environments. Would love to heard from people who have used it.
- New AI edits images based on text instructions (instructPix2Pix/imaginAIry)
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Tensorbook
R.I.P. battery.
Personally I've been using Brev [1] to do my cloud training, you get a cloud GPU instance that you can upgrade/downgrade on the fly, and makes supports VS Code out of the box.
[1] https://brev.dev/
- Brev
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?
EasyLM - Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.
llama.cpp - LLM inference in C/C++
sd_dreambooth_extension
ggml - Tensor library for machine learning
SRNet - A tensorflow reproducing of paper “Editing Text in the wild”
tvm - Open deep learning compiler stack for cpu, gpu and specialized accelerators
open_llama - OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
stable-diffusion-webui - Stable Diffusion web UI
llama-cpp-python - Python bindings for llama.cpp
modal-examples - Examples of programs built using Modal
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.