Update README.md

Adding a clearer instructions to extract probabilities and labels.

README.md

@@ -65,6 +65,8 @@ $ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: applica
 Or Python API:
 
 ```
+import torch
+import torch.nn.functional as F
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
 
 model = AutoModelForSequenceClassification.from_pretrained("madhurjindal/autonlp-Gibberish-Detector-492513457", use_auth_token=True)
@@ -74,4 +76,26 @@ tokenizer = AutoTokenizer.from_pretrained("madhurjindal/autonlp-Gibberish-Detect
 inputs = tokenizer("I love Machine Learning!", return_tensors="pt")
 
 outputs = model(**inputs)
+
+probs = F.softmax(outputs.logits, dim=-1)
+
+predicted_index = torch.argmax(probs, dim=1).item()
+
+predicted_prob = probs[0][predicted_index].item()
+
+labels = model.config.id2label
+
+predicted_label = labels[predicted_index]
+
+for i, prob in enumerate(probs[0]):
+    print(f"Class: {labels[i]}, Probability: {prob:.4f}")
+```
+
+Another simplifed solution with transformers pipline:
+
+```
+from transformers import pipeline
+selected_model = "madhurjindal/autonlp-Gibberish-Detector-492513457"
+classifier = pipeline("text-classification", model=selected_model)
+classifier("I love Machine Learning!")
 ```