README.md

---
library_name: onnx
tags:
  - text2text-generation
  - t5
  - coedit
  - grammar-correction
  - encoder-decoder
  - onnx
  - inference4j
license: apache-2.0
pipeline_tag: text2text-generation
---

# CoEdIT Base — ONNX

ONNX export of [jbochi/coedit-base](https://huggingface.co/jbochi/coedit-base) (250M parameters) with encoder-decoder architecture and KV cache support.

CoEdIT is a T5-based model fine-tuned on the [grammarly/coedit](https://huggingface.co/datasets/grammarly/coedit) dataset for text editing tasks including grammar correction, simplification, coherence, and paraphrasing. This base variant is fine-tuned from `google/flan-t5-base`.

Converted for use with [inference4j](https://github.com/inference4j/inference4j), an inference-only AI library for Java.

## Original Source

- **Repository:** [jbochi/coedit-base](https://huggingface.co/jbochi/coedit-base)
- **License:** Apache 2.0

## Usage with inference4j

```java
try (var corrector = CoeditGrammarCorrector.coeditBase().build()) {
    System.out.println(corrector.correct("She don't likes swimming."));
    // She doesn't like swimming.
}
```

## Model Details

| Property | Value |
|----------|-------|
| Architecture | T5 encoder-decoder (250M parameters) |
| Base model | google/flan-t5-base |
| Training data | grammarly/coedit |
| Task | Grammar correction, text editing |
| Tokenizer | SentencePiece (32,128 tokens) |
| Original framework | PyTorch (transformers) |
| Export method | Hugging Face Optimum (encoder-decoder with KV cache) |

## License

This model is licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). Original model by [jbochi](https://huggingface.co/jbochi), trained on the [Grammarly CoEdIT dataset](https://huggingface.co/datasets/grammarly/coedit).