textgenrnn | Easily train your own text-generating neural network | Machine Learning library
kandi X-RAY | textgenrnn Summary
kandi X-RAY | textgenrnn Summary
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code, or quickly train on a text using a pretrained model.
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Top functions reviewed by kandi - BETA
- Train a neural network
- Train a new model
- Generate an RNN model
- Create a new RNN layer
- Synthesize textgens to a file
- Sample text generation from preds
- Synthesize textgen
- Generate text generator
- Computes the similarity between two texts
- Encodes a list of texts
- Encodes a sequence of text
- Generate a text file
- Generate text
- Generate text samples
- Generate samples
- Train a model from a LTI file
- Load the model
textgenrnn Key Features
textgenrnn Examples and Code Snippets
Lines of Code : 7License : Non-SPDX (NOASSERTION)
Copy* * * incoming message * * *
The Marathon is equipped with three artificial intelligence units. Tycho handles the science and engineering network, Durandal controls the marathon autonomous functions such as doors, air from kitchens, and I don't reme $ rm -r textgenrnn
$ pip install textgenrnn
textgen = textgenrnn(name=marselo)
textgen = textgenrnn(name='marselo')
textgen = textgenrnn(name=model_name)
pip3 instal tensorflow-gpu==1.14
output = t.generate(1, temperature=.5, return_as_list=True)
for string in output:
print(string)
Community Discussions
Trending Discussions on textgenrnn
QUESTION
I was running a Heroku app that gets YouTube video titles and outputs it to a dataset file, it then generates a batch of titles from the dataset. I am using tensorflow 2.0.0.
When I deploy the app and watch the logs (Heroku CLI) I get the following error:
...ANSWER
Answered 2020-Jun-09 at 09:59I use tensorflow==2.0.0.
AttributeError: module 'tensorflow_core._api.v2.config' has no attribute 'get_visible_devices'
tensorflow==2.0.0 does not have have get_visible_devices
tensorflow==2.2.0 has get_visible_devices
see:
https://www.tensorflow.org/api_docs/python/tf/config/get_visible_devices
https://www.tensorflow.org/versions/r2.0/api_docs/python/tf
QUESTION
I have a web app created with django that is using tensorflow to generate compliments and text them to people who sign up for the service. Every time a user submits a number, I'm using subprocess.call() to run a separate script which creates my model and writes the AI-generated compliment to a text file, then the SMS gateway (twilio) uses this .txt file for the body of the message.
However, after submitting a valid number when it is running the model the app is loading for a very long time, like sometimes it takes 30 seconds or longer before the page stops loading and this is not ideal.
Why is this taking so long? Is it because creating the model in tensorflow is just a timely process? And can I do something to speed this up, should I just have it run the code to create the model earlier in the program, or should I just generate a whole bunch of compliments ahead of time and have the SMS gateway draw from that instead?
This is the script which creates the model:
...ANSWER
Answered 2020-May-11 at 09:14It looks like your Tensorflow model is just that slow on this machine. You tested it without Django and it also needs 30 seconds, so we can skip the Django part here.
The best option to make it faster is to use tensorflow-gpu and a server with a Nvidia graphics card (e.g. AWS GPU instances). This usually reduces the needed time by a factor of at least 10, so you will get a waiting time that is probably acceptable for your application.
In addition you should try to decouple Django and the Tensorflow-Script to avoid loading and initializing the model for each request. Create some kind of queue system. Then your Django app write the input value into the queue and waits for the result and your Tensorflow program runs in the background and reads the values from the queue, evaluates the model and sends the result back to Django.
QUESTION
I'm not very experienced using Tensorflow, and I started using a Google Colab created by Max Woolf (https://minimaxir.com/2018/05/text-neural-networks/)
I've edited this post before as I had another simple error I corrected, but then now a bunch of new problems arose with that correction. I'm not experienced as I said, and there's a ton of errors I cannot understand.
I'm trying to train my machine to produce text from a training data file called "marselo", and I suddenly get this error:
...ANSWER
Answered 2020-Apr-08 at 12:44textgen = textgenrnn(name=marselo)
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install textgenrnn
You can use textgenrnn like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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