Update README.md

README.md

@@ -4,7 +4,7 @@ license: cc-by-nc-4.0
 
 # Model Card for Spivavtor-Large
 
-This model was obtained by fine-tuning the corresponding `bigscience/mt0-large` model on the Spivavtor dataset. All deetails of the dataset used and the fine tuned model can be found in our paper and repository.
+This model was obtained by fine-tuning the corresponding `bigscience/mt0-large` model on the Spivavtor dataset. All details of the dataset and fine tuning process can be found in our paper and repository.
 
 **Paper:** Spivavtor: An Instruction Tuned Ukrainian Text Editing Model
 
@@ -14,5 +14,38 @@ This model was obtained by fine-tuning the corresponding `bigscience/mt0-large`
 
 ### Model Description
 
-- **Language(s) (NLP)**: Ukrainian
+- **Language**: Ukrainian
 - **Finetuned from model:** bigscience/mt0-large
+
+## How to use
+We make available the following models presented in our paper. 
+
+<table>
+  <tr>
+    <th>Model</th>
+    <th>Number of parameters</th>
+    <th>Reference name in Paper</th>
+  </tr>
+  <tr>
+    <td>Spivavtor-large</td>
+    <td>1.2B</td>
+    <td>Spivavtor-mt0-large</td>
+  </tr>
+  <tr>
+    <td>Spivavtor-xxl</td>
+    <td>11B</td>
+    <td>Spivavtor-aya-101</td>
+  </tr>  
+</table>
+
+## Usage
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+tokenizer = AutoTokenizer.from_pretrained("grammarly/spivavtor-large")
+model = AutoModelForSeq2SeqLM.from_pretrained("grammarly/spivavtor-large")
+
+input_text = 'Виправте граматику в цьому реченнi: Дякую за iнформацiю! ми з Надiєю саме вийшли з дому'
+
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+outputs = model.generate(input_ids, max_length=256)
+output_text = tokenizer.decode(outputs[0], skip_special_tokens=True)