mixture-of-experts
transformers
| mixture-of-experts | transformers | |
|---|---|---|
| 2 | 176 | |
| 835 | 125,369 | |
| - | 1.7% | |
| 5.3 | 10.0 | |
| 16 days ago | 2 days ago | |
| Python | Python | |
| GNU General Public License v3.0 only | Apache License 2.0 |
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mixture-of-experts
- [Rumor] Potential GPT-4 architecture description
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Local and Global loss
I have a requirement of training pipeline similar to Mixture of Experts (https://github.com/davidmrau/mixture-of-experts/blob/master/moe.py) but I want to train the Experts on a local loss for 1 epoch before predicting outputs from them (which would then be concatenated for the global loss of MoE). Can anyone suggest what’s the best way to set up this training pipeline?
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?
pytorch-tutorial - PyTorch Tutorial for Deep Learning Researchers
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
mmdetection - OpenMMLab Detection Toolbox and Benchmark
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
hivemind - Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.
llama - Inference code for Llama models
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
transformer-pytorch - Transformer: PyTorch Implementation of "Attention Is All You Need"
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
tutel - Tutel MoE: An Optimized Mixture-of-Experts Implementation
huggingface_hub - The official Python client for the Huggingface Hub.