Update README.md

README.md

@@ -2,9 +2,28 @@
 tags: autotrain
 language: en
 widget:
-- text: "I love AutoTrain 🤗"
+- text: "I am still waiting on my card?"
 datasets:
-- philschmid/autotrain-data-does-it-work
+- banking77
+model-index:
+- name: BERT-Banking77
+  results:
+  - task: 
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: "BANKING77" 
+      type: banking77
+    metrics:
+       - name: Accuracy
+         type: accuracy
+         value: 91.99
+       - name: Macro F1
+         type: macro-f1
+         value: 91.99
+       - name: Weighted F1
+         type: weighted-f1
+         value: 91.99
 co2_eq_emissions: 5.632805352029529
 ---
 
@@ -40,13 +59,10 @@ $ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: applica
 Or Python API:
 
 ```
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
-
-model = AutoModelForSequenceClassification.from_pretrained("philschmid/autotrain-does-it-work-940131045", use_auth_token=True)
-
-tokenizer = AutoTokenizer.from_pretrained("philschmid/autotrain-does-it-work-940131045", use_auth_token=True)
-
-inputs = tokenizer("I love AutoTrain", return_tensors="pt")
-
-outputs = model(**inputs)
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+model_id = 'philschmid/DistilBERT-Banking77'
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForSequenceClassification.from_pretrained(model_id)
+classifier = pipeline('text-classification', tokenizer=tokenizer, model=model)
+classifier('What is the base of the exchange rates?')
 ```