DeBERTa
transformers
| DeBERTa | transformers | |
|---|---|---|
| 4 | 176 | |
| 1,847 | 125,021 | |
| 1.0% | 1.4% | |
| 3.6 | 10.0 | |
| 7 months ago | 7 days ago | |
| Python | Python | |
| MIT License | 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.
DeBERTa
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🚀 Microsoft AI Introduce DeBERTa-V3: A Novel Pre-Training Paradigm for Language Models Based on the Combination of DeBERTa and ELECTRA
Quick Read: https://www.marktechpost.com/2023/03/23/microsoft-ai-introduce-deberta-v3-a-novel-pre-training-paradigm-for-language-models-based-on-the-combination-of-deberta-and-electra/ Paper: https://arxiv.org/pdf/2111.09543.pdf Github: https://github.com/microsoft/DeBERTa
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How do I fine-tune zero shot models?
The obvious answer is to look at how the Deberta model was trained for MNLI and copy that: github
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[D] Paper Explained - DeBERTa: Decoding-enhanced BERT with Disentangled Attention (Full Video Analysis)
Code: https://github.com/microsoft/DeBERTa
- DeBERTa-0.9b/1.5b checkpoints released (SuperGLUE score: 89.9%)
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?
clip-as-service - 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
BERTweet - BERTweet: A pre-trained language model for English Tweets (EMNLP-2020)
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
llama - Inference code for Llama models
gector - Official implementation of the papers "GECToR – Grammatical Error Correction: Tag, Not Rewrite" (BEA-20) and "Text Simplification by Tagging" (BEA-21)
transformer-pytorch - Transformer: PyTorch Implementation of "Attention Is All You Need"
sapbert - [NAACL'21 & ACL'21] SapBERT: Self-alignment pretraining for BERT & XL-BEL: Cross-Lingual Biomedical Entity Linking.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
spokestack-python - Spokestack is a library that allows a user to easily incorporate a voice interface into any Python application with a focus on embedded systems.
huggingface_hub - The official Python client for the Huggingface Hub.