textgenrnn
d2l-en
| textgenrnn | d2l-en | |
|---|---|---|
| 7 | 6 | |
| 4,943 | 21,704 | |
| - | 1.3% | |
| 0.0 | 8.5 | |
| almost 2 years ago | 10 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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textgenrnn
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Modern alternative to textgenrnn?
Try this: 1) (Not sure if that's necessary.) Uninstall textgenrnn: pip3 uninstall textgenrnn. 2) Install it using one of this commands: * pip3 install git+git://github.com/minimaxir/textgenrnn.git * pip3 install git+https://github.com/minimaxir/textgenrnn.git (Try the first one, but if it'll raise an error, try the second one.) That's discussion about this "multi_gpu_model not found" error: https://github.com/minimaxir/textgenrnn/issues/222.
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How do you get a Python IDE to execute Python code?
Thanks! PyCharm seems to work well enough. However, I'm not sure how to run an existing project. I successfully imported this github release: https://github.com/minimaxir/textgenrnn But I don't see any "main" file that can be executed. If I run the "setup.py" file, it complains that there is "no command to be executed." Also, import commands seem to fail, even though I literally have the files in the project that I'm trying to import. :/ I don't know how I'm supposed to run commands defined in the project if they can't be imported into a script.
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I trained a neural network on every town and village name in England and then made a website that lets you generate them
This is an utterly fantastic question but I actually don't understand much about neural nets at all, and am just using a prebuilt python library is basically text based neural nets for idiots (https://github.com/minimaxir/textgenrnn) Happy to share data though if you want to find this out and would know how?
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The Office - an episode generated by NN
Python package: Textgenrnn
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makeitmetal.net - A metal band name generator using Python/Tensorflow
I started off with the model from textgenrnn, which is an RNN with LSTM layers. I'm not an expert on deep learning or different model architectures, and textgenrnn is a great starting point because you can use pretrained weights as a starting point for your model. I tweaked the model architecture slightly to allow multiple context labels, but most of the work on this project was porting the model to TensorFlow.js so it could run in the browser once I'd trained it in Python.
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What's wrong with my import?
Is it installed? https://github.com/minimaxir/textgenrnn#usage
d2l-en
- which book to chose for deep learning :lan Goodfellow or francois chollet
- d2l-en: Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.
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How to pre-train BERT on different objective tasks using HuggingFace
There might is bert library for pre-train bert model in huggingface, But I suggestion that you train bert model in native pytorch to understand detail, Limu's course is recommended for you
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The Transformer in Machine Translation
GitHub's article on Dive into Deep Learning
- D2l-En
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I created a way to learn machine learning through Jupyter
There are actually some online books and courses built on Jupyter Notebook ([Dive to Deep Learning Book](https://github.com/d2l-ai/d2l-en) for example). However yours is more detail and could really helps beginners.
What are some alternatives?
gpt-2-simple - Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
deepface - A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
DeepADoTS - Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
Spectrum - Spectrum is an AI that uses machine learning to generate Rap song lyrics
TF-Watcher - Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle
DeepAA - make ASCII Art by Deep Learning
99-ML-Learning-Projects - A list of 99 machine learning projects for anyone interested to learn from coding and building projects
autokeras - AutoML library for deep learning
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
build_a_neural_net_live - The LSTM Neural net code for @Sirajology on Youtube's live video
petastorm - Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.