tf-transformers
State of the art faster Transformer with Tensorflow 2.0 ( NLP, Computer Vision, Audio ). (by legacyai)
bertviz
BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.) (by jessevig)
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| tf-transformers | bertviz | |
|---|---|---|
| 5 | 15 | |
| 84 | 6,377 | |
| - | - | |
| 1.7 | 3.9 | |
| about 1 year ago | 8 months ago | |
| Jupyter Notebook | Python | |
| Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
tf-transformers
Posts with mentions or reviews of tf-transformers.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-03-12.
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Tensorflow-Transformers 2.0 ( for NLP, CV, Audio )
Code : GitHub - legacyai/tf-transformers: State of the art faster Natural Language Processing in Tensorflow 2.0 . 1 Website : https://legacyai.github.io/tf-transformers 1
- [P] Production Ready NLP Deep learning tutorials on tensorflow 2.0. tf-transformers
- Do we really need to Dstill Language Models? Joint loss is all we need - Albert-Joint .
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tf-transformers : State of the art faster NLP in Tensorflow 2.0 . 80 % faster to existing TF based libraries.
Faster Auto Regressive Decoding using Tensorflow2. Faster than PyTorch in most experiments (V100 GPU). 80% faster compared to existing TF based libraries (relative difference) Refer benchmark code.
- [D] Why is tensorflow so hated on and pytorch is the cool kids framework?
bertviz
Posts with mentions or reviews of bertviz.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-05-17.
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StreamingLLM: tiny tweak to KV LRU improves long conversations
This seems only to work cause large GPTs have redundant, undercomplex attentions. See this issue in BertViz about attention in Llama: https://github.com/jessevig/bertviz/issues/128
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[D] Is there a tool that indicates which parts of the input prompt impact the LLM's output the most?
https://github.com/jessevig/bertviz this could be helpful .. I was playing around with it a while ago to see how the attention weights are distributed across prompts
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Show HN: Fully client-side GPT2 prediction visualizer
It would be interesting to have attention visualized as well, similar to how it's done in BertViz:
https://github.com/jessevig/bertviz
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How to visualise LLMs ?
link for lazy: https://github.com/jessevig/bertviz
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Ask HN: Can someone ELI5 Transformers and the “Attention is all we need” paper
The Illustrated Transfomer ( https://jalammar.github.io/illustrated-transformer/ ) and Visualizing attention ( https://towardsdatascience.com/deconstructing-bert-part-2-vi... ), are both really good resources. For a more ELI5 approach this non-technical explainer ( https://www.parand.com/a-non-technical-explanation-of-chatgp... ) covers it at a high level.
- Perplexity.ai Prompt Leakage
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[Discussion] is attention an explanation?
You can get some information this way, but not everything you would want to know. You can try it yourself with BertViz.
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using bert for relation extraction
2) BERT learns a lot in its embeddings: the BERTOLOGY paper (https://arxiv.org/abs/2002.12327) provides a great in-depth look at some of the broader linguistic traits that BERT learns. Different layers often learn different patterns, so the embeddings aren't really interpretable, but you can use something like bertviz (https://github.com/jessevig/bertviz) to explore attention weights across layers for predetermined examples
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Maintaining context vs. overloading your Replika
I messed up a few things and mixed a couple others, anyways this site has a lot of decent information about it. https://towardsdatascience.com/deconstructing-bert-part-2-visualizing-the-inner-workings-of-attention-60a16d86b5c1
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[D] code to visualize attention heads
Big fan of BertViz for this, widely used in research for this very purpose: https://github.com/jessevig/bertviz
What are some alternatives?
When comparing tf-transformers and bertviz you can also consider the following projects:
medspacy - Library for clinical NLP with spaCy.
ecco - Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0).
flax - Flax is a neural network library for JAX that is designed for flexibility.
FARM - :house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.
MIRNet-TFJS - TensorFlow JS models for MIRNet for low-light💡 image enhancement
BERT-pytorch - Google AI 2018 BERT pytorch implementation
BERT-for-Mobile - Compares the DistilBERT and MobileBERT architectures for mobile deployments.
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
gpt-3-simple-tutorial - Generate SQL from Natural Language Sentences using OpenAI's GPT-3 Model
transformer-pytorch - Transformer: PyTorch Implementation of "Attention Is All You Need"
DeBERTa - The implementation of DeBERTa
tf-transformers vs medspacy
bertviz vs ecco
tf-transformers vs flax
bertviz vs FARM
tf-transformers vs MIRNet-TFJS
bertviz vs BERT-pytorch
tf-transformers vs BERT-for-Mobile
bertviz vs transformers
tf-transformers vs gpt-3-simple-tutorial
bertviz vs transformer-pytorch
tf-transformers vs transformers
bertviz vs DeBERTa