Update README.md

README.md

@@ -8,8 +8,7 @@ model-index:
   results: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+
 
 # multichoice-question-generator
 
@@ -22,8 +21,35 @@ It achieves the following results on the evaluation set:
 More information needed
 
 ## Intended uses & limitations
+This is an early version of a model meant to generate multichoice questions from text
+To load the model: 
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("Gachomba/multichoice-question-generator")
+model = AutoModelForSeq2SeqLM.from_pretrained("Gachomba/multichoice-question-generator")
+# tokenize input text
+import torch
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+def tokenize_input(input_text):
+    inputs = tokenizer(input_text, return_tensors="pt", truncation=True, padding='max_length', max_length=1024)
+    return inputs.input_ids.to(device), inputs.attention_mask.to(device)
+
+# generate output from the model
+def generate_output(input_text):
+    input_ids, attention_mask = tokenize_input(input_text)
+    outputs = model.generate(input_ids=input_ids, attention_mask=attention_mask, max_length=512)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# get user input and generate a response
+def get_response():
+    user_input = input("Enter your text: ")
+    response = generate_output(user_input)
+    print("Generated Output:", response)
+
+get_response()
+
 
-More information needed
 
 ## Training and evaluation data