Update README

README.md

@@ -46,6 +46,25 @@ model-index:
 ---
 ## `bart-base-samsum`
 This model was obtained by fine-tuning `facebook/bart-base` on Samsum dataset.
+
+## Usage
+```python
+from transformers import pipeline
+
+summarizer = pipeline("summarization", model="lidiya/bart-base-samsum")
+conversation = '''Jeff: Can I train a 🤗 Transformers model on Amazon SageMaker? 
+Philipp: Sure you can use the new Hugging Face Deep Learning Container. 
+Jeff: ok.
+Jeff: and how can I get started? 
+Jeff: where can I find documentation? 
+Philipp: ok, ok you can find everything here. https://huggingface.co/blog/the-partnership-amazon-sagemaker-and-hugging-face                                           
+'''
+nlp(conversation)
+```
+
+## Training procedure
+- Colab notebook: https://colab.research.google.com/drive/1RInRjLLso9E2HG_xjA6j8JO3zXzSCBRF?usp=sharing
+
 ## Hyperparameters
 ```json
 {
@@ -57,7 +76,6 @@ This model was obtained by fine-tuning `facebook/bart-base` on Samsum dataset.
     "learning_rate": 2e-05,
     "model_name_or_path": "facebook/bart-base",
     "num_train_epochs": 1,
-    "output_dir": "/opt/ml/model",
     "per_device_eval_batch_size": 4,
     "per_device_train_batch_size": 4,
     "predict_with_generate": true,
@@ -65,19 +83,7 @@ This model was obtained by fine-tuning `facebook/bart-base` on Samsum dataset.
     "weight_decay": 0.01,
 }
 ```
-## Usage
-```python
-from transformers import pipeline
-summarizer = pipeline("summarization", model="lidiya/bart-base-samsum")
-conversation = '''Jeff: Can I train a 🤗 Transformers model on Amazon SageMaker? 
-Philipp: Sure you can use the new Hugging Face Deep Learning Container. 
-Jeff: ok.
-Jeff: and how can I get started? 
-Jeff: where can I find documentation? 
-Philipp: ok, ok you can find everything here. https://huggingface.co/blog/the-partnership-amazon-sagemaker-and-hugging-face                                           
-'''
-nlp(conversation)
-```
+
 ## Results
 | key | value |
 | --- | ----- |