How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="gagan3012/k2t-base")
# Load model directly
from transformers import AutoTokenizer, AutoModelWithLMHead

tokenizer = AutoTokenizer.from_pretrained("gagan3012/k2t-base")
model = AutoModelWithLMHead.from_pretrained("gagan3012/k2t-base")
Quick Links

keytotext

keytotext (1)

Idea is to build a model which will take keywords as inputs and generate sentences as outputs.

Keytotext is powered by Huggingface ๐Ÿค—

pypi Version Downloads Open In Colab Streamlit App

Model:

Keytotext is based on the Amazing T5 Model:

Training Notebooks can be found in the Training Notebooks Folder

Usage:

Example usage: Open In Colab

Example Notebooks can be found in the Notebooks Folder

pip install keytotext

carbon (3)

UI:

UI: Streamlit App

pip install streamlit-tags

This uses a custom streamlit component built by me: GitHub

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