mlc-llm
Open-Llama
| mlc-llm | Open-Llama | |
|---|---|---|
| 89 | 7 | |
| 17,053 | 637 | |
| 3.7% | - | |
| 9.9 | 10.0 | |
| 4 days ago | 12 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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.
mlc-llm
- FLaNK 04 March 2024
-
Ai on a android phone?
This one uses gpu, it doesn't support Mistral yet: https://github.com/mlc-ai/mlc-llm
-
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.
-
[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
-
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
-
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.
-
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.
-
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?
Open-Llama
-
(1/2) May 2023
Training code of the open-source high-performance Llama model, including the full process from pre-training to RLHF (https://github.com/s-JoL/Open-Llama)
- Open-Lamam: A “real” open-source project to train LLM not just checkpoints
- Open-Lamam: A real open-source project to train LLM
- Open-Llama: A Open Source Project for Training Language Models
-
OpenLLaMA: An Open Reproduction of LLaMA
Really exciting how fast fully pre-trained new models are appearing.
Here's another repo (with the same "open-llama" name) that has been available on hugging face as well for a few weeks. (different training dataset)
https://github.com/s-JoL/Open-Llama
-
Build your onw LLM 101
Open-Llama
- Open-Llama is an open source project that provides a complete set of training processes for building large-scale language models, from data preparation to tokenization, pre-training, instruction tuning, and reinforcement learning techniques such as RLHF.
What are some alternatives?
llama.cpp - LLM inference in C/C++
open_llama - OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset
ggml - Tensor library for machine learning
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
tvm - Open deep learning compiler stack for cpu, gpu and specialized accelerators
My-Medium-Articles-Friendly-Links - Friendly link to all of my medium articles
AgileRL - Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
llama-cpp-python - Python bindings for llama.cpp
promptfoo - Test your prompts, models, and RAGs. Catch regressions and improve prompt quality. LLM evals for OpenAI, Azure, Anthropic, Gemini, Mistral, Llama, Bedrock, Ollama, and other local & private models with CI/CD integration.
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
EasyLM - Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.