Update README.md

README.md

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 ---
 license: apache-2.0
+datasets:
+- asset
+- wi_locness
+- GEM/wiki_auto_asset_turk
+- discofuse
+- zaemyung/IteraTeR_plus
+language:
+- en
+metrics:
+- sari
+- bleu
+- accuracy
 ---
+# Model Card for CoEdIT-Large
+
+This model was obtained by fine-tuning the corresponding google/flan-t5-large model on the CoEdIT dataset.
+
+Paper: CoEdIT: ext Editing by Task-Specific Instruction Tuning
+Authors: Vipul Raheja, Dhruv Kumar, Ryan Koo, Dongyeop Kang
+
+## Model Details
+
+### Model Description
+
+- **Language(s) (NLP)**: English
+- **Finetuned from model:** google/flan-t5-large
+
+### Model Sources [optional]
+
+- **Repository:** https://github.com/vipulraheja/coedit
+- **Paper [optional]:** [More Information Needed]
+
+## How to use
+We make available the models presented in our paper. 
+
+<table>
+  <tr>
+    <th>Model</th>
+    <th>Number of parameters</th>
+  </tr>
+  <tr>
+    <td>CoEdIT-large</td>
+    <td>770M</td>
+  </tr>
+  <tr>
+    <td>CoEdIT-xl</td>
+    <td>3B</td>
+  </tr>
+  <tr>
+    <td>CoEdIT-xxl</td>
+    <td>11B</td>
+  </tr>  
+</table>
+
+
+## Uses
+
+## Text Revision Task
+Given an edit instruction and an original text, our model can generate the edited version of the text.<br>
+
+![task_specs](https://huggingface.co/grammarly/coedit-xl/resolve/main/Screen%20Shot%202023-05-12%20at%203.36.37%20PM.png)
+
+## Usage
+```python
+from transformers import AutoTokenizer, T5ForConditionalGeneration
+
+tokenizer = AutoTokenizer.from_pretrained("grammarly/coedit-large")
+model = T5ForConditionalGeneration.from_pretrained("grammarly/coedit-large")
+input_text = 
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+outputs = model.generate(input_ids, max_length=256)
+edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)[0]
+
+before_input = 'Fix grammatical errors in this sentence: New kinds of vehicles will be invented with new technology than today.'
+model_input = tokenizer(before_input, return_tensors='pt')
+model_outputs = model.generate(**model_input, num_beams=8, max_length=1024)
+after_text = tokenizer.batch_decode(model_outputs, skip_special_tokens=True)[0]
+```
+
+
+#### Software
+https://github.com/vipulraheja/coedit
+
+## Citation
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]