Update README.md

README.md

@@ -19,17 +19,25 @@ We used the whole Recipe1M+ dataset with a total of 1,029,720 records, with usin
 It achieves the following results on the evaluation set:
 - Loss: 0.6230
 
-## Model description
+## Usage
 
-More information needed
+You can use this model to get embeddings/representations for your food-related dataset that you will use if for your downstream tasks.
 
-## Intended uses & limitations
+```python
+from transformers import pipeline
 
-More information needed
+# Your food-related data
+food_data = "Hawaiian Pizza"
+# Use pipeline for feature extraction
+embedding = pipeline(
+        'feature-extraction', model='alexdseo/RecipeBERT', framework='pt'
+    )
+# Meal pooling
+food_rep = embedding(food_data, return_tensors='pt')[0].numpy().mean(axis=0)
+
+```
 
-## Training and evaluation data
 
-More information needed
 
 ## Training procedure