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@@ -22,5 +22,21 @@ This model is finetuned on a subset from [microsoft/orca-agentinstruct-1M-v1](ht
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  ## Use
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  ```python3
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-
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
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  ## Use
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  ```python3
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+ import torch
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+ from transformers import pipeline
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+ "
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+ pipe = pipeline(
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+ "text-generation",
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+ model=model_id,
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+ torch_dtype=torch.bfloat16,
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+ device_map="auto",
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+ )
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+ messages = [
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+ {"role": "user", "content": "\n\nYou are an expert text classifier. You need to classify the text below into one of the given classes. \n\nText:\n\nThe anticipation of the meteor shower has filled the astronomy club with an infectious excitement, as we prepare our telescopes for what could be a once-in-a-lifetime celestial event.\n\nClasses:\n\nAffirmative Sentiment;Mildly Affirmative Sentiment;Exuberant Endorsement;Objective Assessment;Critical Sentiment;Subdued Negative Sentiment;Intense Negative Sentiment;Ambivalent Sentiment;Sarcastic Sentiment;Ironical Sentiment;Apathetic Sentiment;Elation/Exhilaration Sentiment;Credibility Endorsement;Apprehension/Anxiety;Unexpected Positive Outcome;Melancholic Sentiment;Aversive Repulsion;Indignant Discontent;Expectant Enthusiasm;Affectionate Appreciation;Anticipatory Positivity;Expectation of Negative Outcome;Nuanced Sentiment Complexity\n\nThe output format must be:\n\nFinal class: {selected_class}\n\n"},
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+ ]
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+ outputs = pipe(
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+ messages,
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+ max_new_tokens=256,
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+ )
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+ print(outputs[0]["generated_text"][-1])
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  ```