fastText
deepmind-research
fastText | deepmind-research | |
---|---|---|
8 | 29 | |
25,505 | 12,859 | |
- | 1.1% | |
6.0 | 0.6 | |
2 months ago | 17 days ago | |
HTML | Jupyter Notebook | |
MIT License | Apache License 2.0 |
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fastText
- FastText Repo Archived
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Pixelfed and Naive Bayes: The Grandfather of Spam Filters Still Making Waves
- trained with cross-entropy, meaning that model scores can be used more effectively as a 'confidence' - e.g. for spam if you want to say something like "if prediction score > X, then filter", Naive Bayes is not ideal due to the 'naive' assumption which makes the scores very un-calibrated (it tends to give extremely high or low confidence scores for most things).
disclaimer: I haven't really thought about NLP for about 3 years so there may be something better than this now
[1] https://github.com/facebookresearch/fastText
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How worried are you about AI taking over music?
fasttext 50
- FLiP Stack Weekly for 06-Jan-2023
- Fasttext: Library for efficient text classification and representation learning
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Reverse Language Reconstructing by Consensus [D] [P]
https://github.com/facebookresearch/fastText the readme may have what I need built in. But not sure. I hate ML documentation. I would love to see data input to data output examples because people expect us to understand their line of thought, and it just doesn't work out that way. This looks like what I need, but I've completely misinterpreted ML documentation many times. Ha
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Virtual Sommelier, text classifier in the browser
To use the model trained with FastText from the browser, it is necessary to load it via WebAssembly. However, you don't require a WebAssembly knowledge as you can use the fasttext.js file which has all the glue code.
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Synonyms.vim: feedback needed.
Having the backend code in the plugin repo, and in python held me off. I wrote it to split vimscript/python from the command that finds the info, as it allows to use powerful tools like fasttext rather than a dictionary.
deepmind-research
- This A.I. Subculture's Motto: Go, Go, Go. The eccentric pro-tech movement known as "Effective Accelerationism" wants to unshackle powerful A.I., and party along the way.
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How worried are you about AI taking over music?
Deepmind 63
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Are there Notebooks of AlphaFold 1?
Found some here and here.
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Trying to port this non-standard Tensorflow model to Pytorch and not sure if I'm missing anything
I am trying to make a physics-simulation model based on DeepMind's research, with its source code found here https://github.com/deepmind/deepmind-research/tree/master/learning_to_simulate . The thing that mainly confuses me is how to properly implement the embedding situation found at https://github.com/deepmind/deepmind-research/blob/master/learning_to_simulate/learned_simulator.py on lines 78 and 152.
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[D] Is it possible to use machine learning to create 3D images for the purpose of 3D printing?
Yes. There's a fair bit of research into using ML to generate 3D models. Early work, like Neural Radiance Fields (NeRF) generated a voxel model, which could be used for 3D printing, but it would be low resolution, like blowing up a tiny image vs an SVG vector file. However, more recent research can generate polygonal models from a video taken of a real object. Polygonal models are much better for 3D printing.
- DeepMind Research – code to accompany DeepMind publications
- Skilful precipitation nowcasting using deep generative models of radar - Dr. Piotr Mirowski - Zoom
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[R] Skilful precipitation nowcasting using deep generative models of radar - Link to a free online lecture by the author in comments (deepmind research published in nature)
Skilful precipitation nowcasting using deep generative models of radar https://www.nature.com/articles/s41586-021-03854-z https://deepmind.com/blog/article/nowcasting https://github.com/deepmind/deepmind-research/tree/master/nowcasting
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Deepmind Open-Sources DM21: A Deep Learning Model For Quantum Chemistry
Github: https://github.com/deepmind/deepmind-research/tree/master/density_functional_approximation_dm21
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[P] Choosing a self-supervised learning framework that's easy to use
BYOL - again, it seems that it's not optimized for running on multiple GPUs.
What are some alternatives?
Opus-MT - Open neural machine translation models and web services
jaxline
synonyms.vim - Finding synonyms of words within vim, save time going back and forth to thesaurus.
dm-haiku - JAX-based neural network library
talk - Group video call for the web. No signups. No downloads. [Moved to: https://github.com/vasanthv/tlk]
RETRO-pytorch - Implementation of RETRO, Deepmind's Retrieval based Attention net, in Pytorch
TRIME - [EMNLP 2022] Training Language Models with Memory Augmentation https://arxiv.org/abs/2205.12674
flax - Flax is a neural network library for JAX that is designed for flexibility.
Gauss - Stable Diffusion macOS native app
alphafold_pytorch - An implementation of the DeepMind's AlphaFold based on PyTorch for research
React - The library for web and native user interfaces.
swav - PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882