shumai
transformers
shumai | transformers | |
---|---|---|
15 | 176 | |
1,122 | 125,021 | |
0.2% | 1.4% | |
2.2 | 10.0 | |
9 months ago | 7 days ago | |
TypeScript | Python | |
MIT License | Apache License 2.0 |
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shumai
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PyTorch Primitives in WebGPU for the Browser
https://github.com/tensorflow/tfjs/tree/master/tfjs-backend-...
([...], tflite-support, tflite-micro)
From facebookresearch/shumai (a JS tensor library) https://github.com/facebookresearch/shumai/issues/122 :
> It doesn't make sense to support anything besides WebGPU at this point. WASM + SIMD is around 15-20x slower on my machine[1]. Although WebGL is more widely supported today, it doesn't have the compute features needed for efficient modern ML (transformers etc) and will likely be a deprecated backend for other frameworks when WebGPU comes online.
tensorflow rust has a struct.Tensor:
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Why do people curse JS so much, but also say it's better than Python
JS for ML actually does exist https://github.com/facebookresearch/shumai
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Breaking Up with Python
> It's really a shame that data science, ML, and notebooks are so wrapped up in it. Otherwise we could jettison the whole thing into space
Although I personally feel Python has its place, I contribute to a project that hopes to diversify the ML/scientific computing space with a TypeScript tensor lib called Shumai: https://github.com/facebookresearch/shumai
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Tinygrad: A simple and powerful neural network framework
Doesn’t really matter for large batch/large model training on GPUs that don’t need much coordination.
But Python speed is one of the main motivations for a JS/TS based ML lib I’m working on: https://github.com/facebookresearch/shumai
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[D] Using JavaScript for ML Training/Research (not in the browser)
As a hedge against CPython never becoming fast, we're creating a project called Shumai that attempts to deeply integrate with a new JavaScript runtime (Bun[3]).
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Python 3.11 is much faster than 3.8
You can expose objects. Here's how it is done in Bun: https://github.com/facebookresearch/shumai/blob/main/shumai/...
We've been using this feature heavily in Shumai.
I think you are vastly overestimating the complexity associated with this (user exposed ref-counting/garbage collection) and may not be totally up to date on what's implemented.
- Shumai: Fast Differentiable Tensor Library in TypeScript with Bun and Flashlight
- Shumai: A fast differentiable tensor library for research in TypeScript and JavaScript
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7% Speedup from Switch to and
This thought is pretty much the exact motivation behind a recent effort I’m helping out with https://github.com/facebookresearch/shumai
transformers
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AI enthusiasm #9 - A multilingual chatbot📣🈸
transformers is a package by Hugging Face, that helps you interact with models on HF Hub (GitHub)
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Maxtext: A simple, performant and scalable Jax LLM
Is t5x an encoder/decoder architecture?
Some more general options.
The Flax ecosystem
https://github.com/google/flax?tab=readme-ov-file
or dm-haiku
https://github.com/google-deepmind/dm-haiku
were some of the best developed communities in the Jax AI field
Perhaps the “trax” repo? https://github.com/google/trax
Some HF examples https://github.com/huggingface/transformers/tree/main/exampl...
Sadly it seems much of the work is proprietary these days, but one example could be Grok-1, if you customize the details. https://github.com/xai-org/grok-1/blob/main/run.py
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Lossless Acceleration of LLM via Adaptive N-Gram Parallel Decoding
The HuggingFace transformers library already has support for a similar method called prompt lookup decoding that uses the existing context to generate an ngram model: https://github.com/huggingface/transformers/issues/27722
I don't think it would be that hard to switch it out for a pretrained ngram model.
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AI enthusiasm #6 - Finetune any LLM you want💡
Most of this tutorial is based on Hugging Face course about Transformers and on Niels Rogge's Transformers tutorials: make sure to check their work and give them a star on GitHub, if you please ❤️
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Schedule-Free Learning – A New Way to Train
* Superconvergence + LR range finder + Fast AI's Ranger21 optimizer was the goto optimizer for CNNs, and worked fabulously well, but on transformers, the learning rate range finder sadi 1e-3 was the best, whilst 1e-5 was better. However, the 1 cycle learning rate stuck. https://github.com/huggingface/transformers/issues/16013
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Gemma doesn't suck anymore – 8 bug fixes
Thanks! :) I'm pushing them into transformers, pytorch-gemma and collabing with the Gemma team to resolve all the issues :)
The RoPE fix should already be in transformers 4.38.2: https://github.com/huggingface/transformers/pull/29285
My main PR for transformers which fixes most of the issues (some still left): https://github.com/huggingface/transformers/pull/29402
- HuggingFace Transformers: Qwen2
- HuggingFace Transformers Release v4.36: Mixtral, Llava/BakLlava, SeamlessM4T v2
- HuggingFace: Support for the Mixtral Moe
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Paris-Based Startup and OpenAI Competitor Mistral AI Valued at $2B
If you want to tinker with the architecture Hugging Face has a FOSS implementation in transformers: https://github.com/huggingface/transformers/blob/main/src/tr...
If you want to reproduce the training pipeline, you couldn't do that even if you wanted to because you don't have access to thousands of A100s.
What are some alternatives?
rosettaboy - A gameboy emulator in several different languages
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
jittor - Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
openpilot - openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for 250+ supported car makes and models.
llama - Inference code for Llama models
devdocs - API Documentation Browser
transformer-pytorch - Transformer: PyTorch Implementation of "Attention Is All You Need"
FrameworkBenchmarks - Source for the TechEmpower Framework Benchmarks project
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
huggingface_hub - The official Python client for the Huggingface Hub.