LLaMA_MPS
web-llm
| LLaMA_MPS | web-llm | |
|---|---|---|
| 4 | 42 | |
| 566 | 9,102 | |
| - | 2.4% | |
| 10.0 | 9.1 | |
| about 1 year ago | 9 days ago | |
| Python | TypeScript | |
| GPL-3.0 | Apache License 2.0 |
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LLaMA_MPS
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A brief history of LLaMA models
Most places that recommend llama.cpp for mac fail to mention https://github.com/jankais3r/LLaMA_MPS, which runs unquantized 7b and 13b models on the M1/M2 GPU directly. It's slightly slower, (not a lot), and significantly lower energy usage. To me the win not having to quantize is huge; I wish more people knew about it.
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Databricks Releases 15K Record Training Corpus for Instruction Tuning LLMs
I saw this: https://github.com/jankais3r/LLaMA_MPS
it runs slightly slower on the GPU than under llama.cpp but uses much less power doing so
I would guess the slowness is due to immaturity of the PyTorch MPS backend, the asitop graphs show it doing a bunch of cpu along with the gpu, so it might be inefficiently falling back to cpu for some ops and swapping layers back and forth (I have no idea, just guessing)
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Apples effort on developing Chat GPT like functions?
Not chatgpt, but also nothing to sneeze at. https://github.com/jankais3r/LLaMA_MPS 7B llm on 32gb m1 pro.
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llama VS LLaMA_MPS - a user suggested alternative
2 projects | 10 Mar 2023
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
What are some alternatives?
llama-mps - Experimental fork of Facebooks LLaMa model which runs it with GPU acceleration on Apple Silicon M1/M2
chainlit - Build Conversational AI in minutes ⚡️
m1xxx - Unofficial native Mixxx builds for macOS (Apple Silicon/Intel) and Linux
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
gpt4all - gpt4all: run open-source LLMs anywhere
RedPajama-Data - The RedPajama-Data repository contains code for preparing large datasets for training large language models.
StableLM - StableLM: Stability AI Language Models
vanilla-llama - Plain pytorch implementation of LLaMA
FastChat - An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
Multi-Modality-Arena - Chatbot Arena meets multi-modality! Multi-Modality Arena allows you to benchmark vision-language models side-by-side while providing images as inputs. Supports MiniGPT-4, LLaMA-Adapter V2, LLaVA, BLIP-2, and many more!
duckdb-wasm - WebAssembly version of DuckDB