NavyaNayer commited on
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79173f1
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1 Parent(s): 9e49caf

Delete complexity_score.py

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  1. complexity_score.py +0 -41
complexity_score.py DELETED
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- <<<<<<< HEAD
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- from transformers import AutoTokenizer, AutoModelForSequenceClassification
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- import torch
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-
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- # Load the tokenizer and model
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- tokenizer = AutoTokenizer.from_pretrained("thethinkmachine/Maxwell-Task-Complexity-Scorer-v0.2")
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- model = AutoModelForSequenceClassification.from_pretrained("thethinkmachine/Maxwell-Task-Complexity-Scorer-v0.2")
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-
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- # Example task
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- task_description = "find a new theory"
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-
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- # Tokenize the input
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- inputs = tokenizer(task_description, return_tensors="pt")
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-
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- # Perform inference
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- with torch.no_grad():
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- outputs = model(**inputs)
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- complexity_score = torch.sigmoid(outputs.logits).item()
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-
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- print(f"Task Complexity Score: {complexity_score:.4f}")
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- =======
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- from transformers import AutoTokenizer, AutoModelForSequenceClassification
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- import torch
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-
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- # Load the tokenizer and model
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- tokenizer = AutoTokenizer.from_pretrained("thethinkmachine/Maxwell-Task-Complexity-Scorer-v0.2")
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- model = AutoModelForSequenceClassification.from_pretrained("thethinkmachine/Maxwell-Task-Complexity-Scorer-v0.2")
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-
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- # Example task
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- task_description = "find a new theory"
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-
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- # Tokenize the input
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- inputs = tokenizer(task_description, return_tensors="pt")
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-
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- # Perform inference
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- with torch.no_grad():
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- outputs = model(**inputs)
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- complexity_score = torch.sigmoid(outputs.logits).item()
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-
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- print(f"Task Complexity Score: {complexity_score:.4f}")
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- >>>>>>> b1313c5d084e410cadf261f2fafd8929cb149a4f