Ursa_Minor0.4

Model Description

Ursa_Minor0.4 is a reasoning-focused language model developed by ExplodingCB2 (Sculptor-AI) and hosted on Hugging Face. It is designed to tackle complex reasoning tasks, demonstrating capabilities in multi-step inference, logical deduction, and contextual understanding.

Key Features:

• Reasoning Prowess: Emphasizes strong reasoning abilities over sheer memorization, aiming for accurate and logical responses.
• Multi-Step Inference: Capable of breaking down complex problems into smaller, manageable steps.
• Logical Deduction: Demonstrates proficiency in applying logical rules and principles to arrive at valid conclusions.
• Contextual Understanding: Exhibits an ability to grasp and utilize contextual information to enhance reasoning accuracy.
• Developed by ExplodingCB2 & Kaileh57 (Sculptor-AI): A model born from focused research and development in the field of AI reasoning.

Intended Uses

• Answering complex questions that require multi-step reasoning.
• Solving logical puzzles and problems.
• Assisting in tasks that demand contextual understanding and inference.
• Research and development in the field of AI reasoning.
• Experimentation with advanced prompting techniques.

How to Use

You can use the Ursa_Minor0.4 model through the Hugging Face Transformers library. Here's a basic example:

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Sculptor-AI/Ursa_Minor")
model = AutoModelForCausalLM.from_pretrained("Sculptor-AI/Ursa_Minor")

prompt = "What are the prime factors of 42?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=50)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)

print(response)