| --- |
| 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) |
| ``` |
