---
library_name: transformers
tags: []
---

# Model Card for Model ID

## Usage
```python
from transformers import AutoTokenizer, T5ForConditionalGeneration, BitsAndBytesConfig
import torch

tokenizer = AutoTokenizer.from_pretrained("wisdominanutshell/coedit-xxl-8bit")
model = T5ForConditionalGeneration.from_pretrained("wisdominanutshell/coedit-xxl-8bit", quantization_config=BitsAndBytesConfig(load_in_8bit=True))
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
input_text = 'Fix grammatical errors in this sentence: When I graw up, I start to understand what he said is quite right.'
input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
outputs = model.generate(input_ids, max_length=256)
edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

print(edited_text)
```

## Model Details

### Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

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## How to Get Started with the Model

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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