update

README.md

@@ -11,7 +11,12 @@ datasets:
 co2_eq_emissions:
   emissions: 0.0015416078395342335
 ---
-
+# Class
+0 - None <br>
+1 - Metrics and Targets  <br>
+2 - Strategy  <br>
+3 - Risk Management  <br>
+4 - Governance  <br>
 # Model Trained Using AutoTrain
 
 - Problem type: Multi-class Classification
@@ -38,7 +43,7 @@ co2_eq_emissions:
 You can use cURL to access this model:
 
 ```
-$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/Sachinkelenjaguri/autotrain-climate-tcfd-recommendation-55122128742
+$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/Sachinkelenjaguri/autotrain-climate-tcfd-recommendation
 ```
 
 Or Python API:
@@ -46,9 +51,9 @@ Or Python API:
 ```
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
 
-model = AutoModelForSequenceClassification.from_pretrained("Sachinkelenjaguri/autotrain-climate-tcfd-recommendation-55122128742", use_auth_token=True)
+model = AutoModelForSequenceClassification.from_pretrained("Sachinkelenjaguri/autotrain-climate-tcfd-recommendation", use_auth_token=True)
 
-tokenizer = AutoTokenizer.from_pretrained("Sachinkelenjaguri/autotrain-climate-tcfd-recommendation-55122128742", use_auth_token=True)
+tokenizer = AutoTokenizer.from_pretrained("Sachinkelenjaguri/autotrain-climate-tcfd-recommendation", use_auth_token=True)
 
 inputs = tokenizer("I love AutoTrain", return_tensors="pt")