Model Card for Model ID
<!-- Briefly summarize what the model is/does. -->
This is an English grammar correction model.
Model Details
Model Description
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- Developed by: Amin Rahmani
- Model type: T5
- Language(s) (NLP): English
- License: MIT
How to Get Started with the Model
from happytransformer import HappyTextToText
happy_tt = HappyTextToText("T5", ".\PATH TO MODEL")
from happytransformer import TTSettings
beam_settings = TTSettings(num_beams=8, min_length=1, max_length=100)
input_text_1 = "grammar: hi dear"
output_text_1 = happy_tt.generate_text(input_text_1, args=beam_settings) print(output_text_1.text)
[More Information Needed]
Training Hyperparameters
- Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
Speeds, Sizes, Times [optional]
validation loss: 0.04 learning rate: epochs: 3
Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type: RTX 3090
