web-llm
mlc-llm
web-llm | mlc-llm | |
---|---|---|
42 | 89 | |
9,102 | 16,955 | |
2.4% | 3.2% | |
9.1 | 9.9 | |
8 days ago | 5 days ago | |
TypeScript | Python | |
Apache License 2.0 | 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.
web-llm
- What stack would you recommend to build a LLM app in React without a backend?
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When LLM doesn’t fit into memory, how to make it work?
So I was playing with MLC webllm locally. I got my mistral 7B model installed and quantised. Converted it using mlc lib to metal package for Apple chips. Now it takes only 3.5GB of memory
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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.
- Local embeddings model for javascript
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this makes deploying AI language models so much easier
Link to github for those who want to know about MLC straight from them. Web demo is cool but takes a long time to load first time. https://github.com/mlc-ai/web-llm
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April 2023
web-llm: Bringing large-language models and chat to web browsers. (https://github.com/mlc-ai/web-llm)
- Running a small model on a phone?
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Weekly Megathread - 14 May 2023
WebLLM - https://mlc.ai/web-llm/
- WebLLM - Bringing LLMs based chatbot to your web browser
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Google is bringing AI to the browser with WebGPU in Chrome
which makes this works in the browser
https://mlc.ai/web-llm/#chat-demo
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?
chainlit - Build Conversational AI in minutes ⚡️
llama.cpp - LLM inference in C/C++
gpt4all - gpt4all: run open-source LLMs anywhere
ggml - Tensor library for machine learning
StableLM - StableLM: Stability AI Language Models
tvm - Open deep learning compiler stack for cpu, gpu and specialized accelerators
FastChat - An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
duckdb-wasm - WebAssembly version of DuckDB
llama-cpp-python - Python bindings for llama.cpp
triton - Development repository for the Triton language and compiler
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.