Transformers
PyTorch
English
t5
text2text-generation
keytotext
k2t-tiny
Keywords to Sentences
text-generation-inference
Instructions to use gagan3012/k2t-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gagan3012/k2t-tiny with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gagan3012/k2t-tiny") model = AutoModelForSeq2SeqLM.from_pretrained("gagan3012/k2t-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
language: en
thumbnail: Keywords to Sentences
tags:
- keytotext
- k2t-tiny
- Keywords to Sentences
license: mit
datasets:
- WebNLG
- Dart
metrics:
- NLG
keytotext
Idea is to build a model which will take keywords as inputs and generate sentences as outputs.
Keytotext is powered by Huggingface 🤗
Model:
Keytotext is based on the Amazing T5 Model:
Training Notebooks can be found in the Training Notebooks Folder
Usage:
Example Notebooks can be found in the Notebooks Folder
pip install keytotext
UI:
pip install streamlit-tags
This uses a custom streamlit component built by me: GitHub


