Update README.md

README.md

@@ -31,4 +31,43 @@ dress him every morning?"],
 }
 ```
 
+##How to use
 
+```bash
+# Installing requirements
+pip install transformers
+```
+
+```python
+from model_file import FlaxGPT2ForMultipleChoice
+model_path="flax-community/gpt2-Cosmos"
+model = FlaxGPT2ForMultipleChoice.from_pretrained(model_path,input_shape=(1,4,1))
+
+run_dataset=Dataset.from_csv('......')
+
+def preprocess(example):
+    example['context&question']=example['context']+example['question']
+    example['first_sentence']=[example['context&question'],example['context&question'],example['context&question'],example['context&question']]
+    example['second_sentence']=example['answer0'],example['answer1'],example['answer2'],example['answer3']
+    return example
+    
+run_dataset=run_dataset.map(preprocess)
+
+def tokenize(examples):
+    a=tokenizer(examples['first_sentence'],examples['second_sentence'],padding='max_length',truncation=True,max_length=256,return_tensors='jax')
+    a['labels']=examples['label']
+    return a
+    
+run_dataset=run_dataset.map(tokenize)
+
+input_id=jnp.array(run_dataset['input_ids'])
+att_mask=jnp.array(run_dataset['attention_mask'])
+
+outputs=model(input_id,att_mask)
+
+final_output=jnp.argmax(outputs,axis=-1)
+
+Print(f"the predction of the dataset : {final_output}")
+```
+  
+