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README.md
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* **Multi-Step Inference:** Capable of breaking down complex problems into smaller, manageable steps.
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* **Logical Deduction:** Demonstrates proficiency in applying logical rules and principles to arrive at valid conclusions.
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* **Contextual Understanding:** Exhibits an ability to grasp and utilize contextual information to enhance reasoning accuracy.
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* **Developed by ExplodingCB2 (Sculptor-AI):** A model born from focused research and development in the field of AI reasoning.
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## Intended Uses
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("Sculptor-AI/
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model = AutoModelForCausalLM.from_pretrained("Sculptor-AI/
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prompt = "What are the prime factors of 42?"
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inputs = tokenizer(prompt, return_tensors="pt")
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* **Multi-Step Inference:** Capable of breaking down complex problems into smaller, manageable steps.
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* **Logical Deduction:** Demonstrates proficiency in applying logical rules and principles to arrive at valid conclusions.
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* **Contextual Understanding:** Exhibits an ability to grasp and utilize contextual information to enhance reasoning accuracy.
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* **Developed by ExplodingCB2 & Kaileh57 (Sculptor-AI):** A model born from focused research and development in the field of AI reasoning.
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## Intended Uses
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("Sculptor-AI/Ursa_Minor")
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model = AutoModelForCausalLM.from_pretrained("Sculptor-AI/Ursa_Minor")
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prompt = "What are the prime factors of 42?"
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inputs = tokenizer(prompt, return_tensors="pt")
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