Update README.md

README.md

@@ -1,5 +1,5 @@
 ---
-license: cc-by-nc-4.0
+license: apache-2.0
 inference:
   parameters:
     num_beams: 2
@@ -40,10 +40,11 @@ T5 model expects a task related prefix: since it is a description generation tas
 
 ```python
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import torch
 
-device = "cuda"
-tokenizer = AutoTokenizer.from_pretrained("Ateeqq/product-description-generator", token='your_token')
-model = AutoModelForSeq2SeqLM.from_pretrained("Ateeqq/product-description-generator", token='your_token').to(device)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+tokenizer = AutoTokenizer.from_pretrained("Ateeqq/product-description-generator")
+model = AutoModelForSeq2SeqLM.from_pretrained("Ateeqq/product-description-generator").to(device)
 
 def generate_description(title):
     input_ids = tokenizer(f'description: {title}', return_tensors="pt", padding="longest", truncation=True, max_length=128).input_ids.to(device)
@@ -100,8 +101,4 @@ generate_description(title)
 
 - **Update Training Data**: Retrain the model using the latest 0.5 million cleaned examples.
 - **Optimize Training Parameters**: Experiment with different batch sizes, learning rates, and epochs to further improve model performance.
-- **Expand Dataset**: Incorporate more diverse product datasets to enhance the model's versatility and robustness.
-
-## License
-
-Limited Use: It grants a non-exclusive, non-transferable license to use the this model. This means you can't freely share it with others or sell the model itself.
+- **Expand Dataset**: Incorporate more diverse product datasets to enhance the model's versatility and robustness.