Instructions to use stephenleejm/T5_yoda_translator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stephenleejm/T5_yoda_translator with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("stephenleejm/T5_yoda_translator") model = AutoModelForSeq2SeqLM.from_pretrained("stephenleejm/T5_yoda_translator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Introduction
This model translate between Yoda-ish to English and vice versa. It makes use of the T5-base model and finetuning. Basically it trains for 2 tasks using the same dataset. In Yoda-ish to English, trains
Dataset
For this first version of the model I used a small sample of 20 Yoda quotes for training. I am in the midst of collecting more samples for training.
Usage
Input
For Yoda-ish to English, you can use the prefix "y_to_e: text" to pass in as the input.
For English to Yodaish you can use the prefix "e_to_y: text"
Output The translated sentence.
E.g
e_to_y: I am sick of you => Sick of you, I am
Spaces
To try this model you can access it here
- Downloads last month
- 4