Update README.md

README.md

@@ -9,14 +9,14 @@ pipeline_tag: summarization
 # Fine-tuned Longformer for Summarization of Machine Learning Articles
 
 ## Model Details
-- GitHub: https://github.com/Bakhitovd/MS_in_Data_Science_Capstone
+- GitHub: https://github.com/Bakhitovd/led-base-7168-ml
 - Model name: bakhitovd/led-base-7168-ml
 - Model type: Longformer (alenai/led-base-16384)
 - Model description: This Longformer model has been fine-tuned on a focused subset of the arXiv part of the scientific papers dataset, specifically targeting articles about Machine Learning. It aims to generate accurate and consistent summaries of machine learning research papers.
 ## Intended Use
 This model is intended to be used for text summarization tasks, specifically for summarizing machine learning research papers.
 ## How to Use
-```
+```python
 import torch
 from transformers import LEDTokenizer, LEDForConditionalGeneration
 tokenizer = LEDTokenizer.from_pretrained("bakhitovd/led-base-7168-ml")
@@ -24,7 +24,7 @@ model = LEDForConditionalGeneration.from_pretrained("bakhitovd/led-base-7168-ml"
 ```
 
 ## Use the model for summarization
-```
+```python
 article = "... long document ..."
 inputs_dict = tokenizer.encode(article, padding="max_length", max_length=16384, return_tensors="pt", truncation=True)
 input_ids = inputs_dict.input_ids.to("cuda")