Update README.md

README.md

@@ -14,4 +14,43 @@ co2_eq_emissions: 39.76330395590446
 # Model Trained Using AutoNLP
 
 - Problem type: Extractive Question Answering
-- CO2 Emissions (in grams): 39.76330395590446
+- CO2 Emissions (in grams): 39.76330395590446
+
+
+## Usage
+
+You can use cURL to access this model:
+
+```
+$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"question": "Who loves AutoNLP?", "context": "Everyone loves AutoNLP"}' https://api-inference.huggingface.co/models/abhishek/autonlp-hindi-question-answering-23865268
+```
+
+Or Python API:
+
+```
+import torch
+
+from transformers import AutoModelForQuestionAnswering, AutoTokenizer
+
+model = AutoModelForQuestionAnswering.from_pretrained("abhishek/autonlp-hindi-question-answering-23865268", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("abhishek/autonlp-hindi-question-answering-23865268", use_auth_token=True)
+
+from transformers import BertTokenizer, BertForQuestionAnswering
+
+question, text = "Who loves AutoNLP?", "Everyone loves AutoNLP"
+
+inputs = tokenizer(question, text, return_tensors='pt')
+
+start_positions = torch.tensor([1])
+
+end_positions = torch.tensor([3])
+
+outputs = model(**inputs, start_positions=start_positions, end_positions=end_positions)
+
+loss = outputs.loss
+
+start_scores = outputs.start_logits
+
+end_scores = outputs.end_logits
+```