README.md

---
license: apache-2.0
datasets:
- agentlans/high-quality-english-sentences
language:
- en
base_model:
- google-t5/t5-base
library_name: transformers
tags:
- Safetensors
---

This model is for typos in texts and it outputs corrected texts.

Example:

Text with Typos: **Whathvhr wh call owr carhaivhrs - doctors, nwrsh practitionhrs, clinicians, - wh nhhd thhm not only to carh, wh nhhd thhm to uh aulh to providh thh riaht valwh.**

Corrected Text: **Whatever we call our caregivers - doctors, nurse practitioners, clinicians, - we need them not only to care, we need them to be able to provide the right value.**


Example Usage:
```py
#Load the model and tokenizer
text = "" #Text with typos here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
```