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Update README.md (#3)

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Co-authored-by: yingshaoxo <[email protected]>

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@@ -53,11 +53,34 @@ Here is how to import this model in Python:
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  <summary> Click to expand </summary>
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  ```python
 
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  from transformers import AutoTokenizer, AutoModelForQuestionAnswering
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  tokenizer = AutoTokenizer.from_pretrained("Intel/dynamic_tinybert")
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-
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  model = AutoModelForQuestionAnswering.from_pretrained("Intel/dynamic_tinybert")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
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  </details>
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  <summary> Click to expand </summary>
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  ```python
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+ import torch
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  from transformers import AutoTokenizer, AutoModelForQuestionAnswering
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  tokenizer = AutoTokenizer.from_pretrained("Intel/dynamic_tinybert")
 
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  model = AutoModelForQuestionAnswering.from_pretrained("Intel/dynamic_tinybert")
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+
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+ context = "remember the number 123456, I'll ask you later."
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+ question = "What is the number I told you?"
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+
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+ # Tokenize the context and question
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+ tokens = tokenizer.encode_plus(question, context, return_tensors="pt", truncation=True)
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+
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+ # Get the input IDs and attention mask
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+ input_ids = tokens["input_ids"]
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+ attention_mask = tokens["attention_mask"]
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+
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+ # Perform question answering
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+ outputs = model(input_ids, attention_mask=attention_mask)
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+ start_scores = outputs.start_logits
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+ end_scores = outputs.end_logits
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+
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+ # Find the start and end positions of the answer
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+ answer_start = torch.argmax(start_scores)
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+ answer_end = torch.argmax(end_scores) + 1
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+ answer = tokenizer.convert_tokens_to_string(tokenizer.convert_ids_to_tokens(input_ids[0][answer_start:answer_end]))
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+
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+ # Print the answer
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+ print("Answer:", answer)
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  ```
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  </details>
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