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:

#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)
Downloads last month
0
Safetensors
Model size
223M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Cipher-AI/AutoCorrect-EN

Base model

google-t5/t5-base
Finetuned
(432)
this model

Dataset used to train Cipher-AI/AutoCorrect-EN