TensorFlowOnSpark
transformers
TensorFlowOnSpark | transformers | |
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2 | 176 | |
3,864 | 125,369 | |
0.1% | 1.7% | |
1.4 | 10.0 | |
10 months ago | about 19 hours ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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TensorFlowOnSpark
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[D]Speed up inference on Spark
Currently I use TensorflowOnSpark frame to train and predict model. When prediction, I have billions of samples to predict which is time-consuming. I wonder if there is some good practices on this.
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[D] Plug or Integrate a GNN Pytorch code base into Spark Cluster
https://github.com/yahoo/TensorFlowOnSpark : check out if this project is useful for you.
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?
ecosystem - Integration of TensorFlow with other open-source frameworks
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
Keras - Deep Learning for humans
llama - Inference code for Llama models
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
transformer-pytorch - Transformer: PyTorch Implementation of "Attention Is All You Need"
mlToolKits - learningOrchestra is a distributed Machine Learning integration tool that facilitates and streamlines iterative processes in a Data Science project.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
huggingface_hub - The official Python client for the Huggingface Hub.
OpenNMT-py - Open Source Neural Machine Translation and (Large) Language Models in PyTorch