pytorch-sentiment-analysis
ecco
| pytorch-sentiment-analysis | ecco | |
|---|---|---|
| 2 | 6 | |
| 4,225 | 1,905 | |
| - | - | |
| 4.0 | 3.6 | |
| about 1 month ago | 3 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | BSD 3-clause "New" or "Revised" License |
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pytorch-sentiment-analysis
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Ich habe einen Bot gebastelt für Ovalwichs
z.B. https://github.com/bentrevett/pytorch-sentiment-analysis
- German language sentiment classification - NLP Deep Learning
ecco
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[D] Visualizing attention
I ran into this a few days ago, might be useful https://github.com/jalammar/ecco
- Show HN: Language model analysis and visualization toolkit
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[P] Ecco - Language model analysis and visualization toolkit
GitHub: https://github.com/jalammar/ecco Paper: https://aclanthology.org/2021.acl-demo.30/
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Finding the Words to Say: Hidden State Visualizations for Language Models
Hello HN, author here. Language models are absolutely fascinating tools. I believe it would pay for software engineers to have a sense of their capabilities and how they function. The article showcases a few views to expose the inner workings of the model, but also simple UI for interacting with a language model to get a sense for how they work and generate words.
If you prefer video, I have also recently released a video [1] with PyData to provide an intro to language models and their applications and how we're trying to make Transformer-based ones more transparent with Ecco[2].
[1] https://www.youtube.com/watch?v=rHrItfNeuh0
[2] https://www.eccox.io/ and https://github.com/jalammar/ecco
Thanks mods for merging submissions. Happy to get feedback , thoughts, or questions.
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Show HN: Ecco – See what your NLP language model is “thinking”
https://github.com/jalammar/ecco/blob/1e957a4c1c9bd49c203993...
What are some alternatives?
spark-nlp - State of the Art Natural Language Processing
bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
Basic-UI-for-GPT-J-6B-with-low-vram - A repository to run gpt-j-6b on low vram machines (4.2 gb minimum vram for 2000 token context, 3.5 gb for 1000 token context). Model loading takes 12gb free ram.
nlp-class - A Natural Language Processing course taught by Professor Ghassemi
Time-Series-Forecasting-Using-LSTM - Time-Series Forecasting on Stock Prices using LSTM
muppetshow
Behavior-Sequence-Transformer-Pytorch - This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf
VisionTransformer-Pytorch
malaya - Natural Language Toolkit for Malaysian language, https://malaya.readthedocs.io/
TabularSemanticParsing - Translating natural language questions to a structured query language
afinn - AFINN sentiment analysis in Python
adaptnlp - An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.