Update README.md

README.md

@@ -21,49 +21,65 @@ as well as Philosophy in Arabic.
 For more details, check out our [example.com](paper)
 
 
-### Pipeline example
+
+### Full classification example
 
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+
 tokenizer = AutoTokenizer.from_pretrained("dru-acrps/ArGTClass")
 model = AutoModelForSequenceClassification.from_pretrained("dru-acrps/ArGTClass", device_map = 'auto')
 
-classifier = pipeline("text-classification", model=model, tokenizer= tokenizer)
-
 text = " .قصفت إسرائيل مستشفى المعمداني في مدينة غزة، والذي خلف مئات الشهداء والجرحى"
 
-classifier(text)
+inputs = tokenizer(text, return_tensors= 'pt')
+outputs = model(**inputs)
+ind = outputs.logits.argmax(dim=-1)[0]
+predicted_class = model.config.id2label[ind.item()]
+```
+
+### Full classification example (GPU)
+
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+
+tokenizer = AutoTokenizer.from_pretrained("dru-acrps/ArGTClass")
+model = AutoModelForSequenceClassification.from_pretrained("dru-acrps/ArGTClass", device_map = 'auto')
+
+text = " .قصفت إسرائيل مستشفى المعمداني في مدينة غزة، والذي خلف مئات الشهداء والجرحى"
 
+inputs = tokenizer(text, return_tensors= 'pt')
+outputs = model(**inputs)
+ind = outputs.logits.argmax(dim=-1)[0]
+predicted_class = model.config.id2label[ind.item()]
 ```
 
 
-### Pipeline example (GPU)
+### Pipeline example
 
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
 tokenizer = AutoTokenizer.from_pretrained("dru-acrps/ArGTClass")
 model = AutoModelForSequenceClassification.from_pretrained("dru-acrps/ArGTClass", device_map = 'auto')
 
-classifier = pipeline("text-classification", model=model, tokenizer= tokenizer, device="cuda:0")
+classifier = pipeline("text-classification", model=model, tokenizer= tokenizer)
 
 text = " .قصفت إسرائيل مستشفى المعمداني في مدينة غزة، والذي خلف مئات الشهداء والجرحى"
 
 classifier(text)
 ```
 
-### Full classification example
+
+### Pipeline example (GPU)
 
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
-
 tokenizer = AutoTokenizer.from_pretrained("dru-acrps/ArGTClass")
 model = AutoModelForSequenceClassification.from_pretrained("dru-acrps/ArGTClass", device_map = 'auto')
 
+classifier = pipeline("text-classification", model=model, tokenizer= tokenizer, device="cuda:0")
+
 text = " .قصفت إسرائيل مستشفى المعمداني في مدينة غزة، والذي خلف مئات الشهداء والجرحى"
 
-inputs = tokenizer(text, return_tensors= 'pt')
-outputs = model(**inputs)
-ind = outputs.logits.argmax(dim=-1)[0]
-predicted_class = model.config.id2label[ind.item()]
+classifier(text)
 ```
-