Update README.md
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README.md
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@@ -59,14 +59,11 @@ import torch
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from unsloth import FastModel
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from transformers import TextStreamer
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-
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# 1. Model and Tokenizer Loading
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max_seq_length = 1024
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model_name = "NuclearAi/Nuke_X_Gemma3_1B_Reasoner_Testing"
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print(f"Loading model: {model_name}...")
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model, tokenizer = FastModel.from_pretrained(
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print("Model loaded.")
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# 2. Define Prompt Structure
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reasoning_start = "<think>"
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solution_start = "<response>"
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solution_end = "</response>"
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system_prompt = \
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f"""You are given a problem.
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@@ -99,7 +94,6 @@ Then, provide your solution between {solution_start}{solution_end}"""
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user_question = "Write a short story about a cat who learns to fly." # Try another question
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# 4. Format Input for Chat Model
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messages = [
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{"role": "system", "content": system_prompt},
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)
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# 5. Tokenize and Prepare for Generation
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device = model.device if hasattr(model, 'device') else ('cuda' if torch.cuda.is_available() else 'cpu')
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inputs = tokenizer([text_input], return_tensors="pt").to(device)
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from unsloth import FastModel
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from transformers import TextStreamer
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# 1. Model and Tokenizer Loading
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max_seq_length = 1024
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model_name = "NuclearAi/Nuke_X_Gemma3_1B_Reasoner_Testing"
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print(f"Loading model: {model_name}...")
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model, tokenizer = FastModel.from_pretrained(
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)
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print("Model loaded.")
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# 2. Define Prompt Structure
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reasoning_start = "<think>"
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solution_start = "<response>"
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solution_end = "</response>"
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system_prompt = \
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f"""You are given a problem.
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user_question = "Write a short story about a cat who learns to fly." # Try another question
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# 4. Format Input for Chat Model
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messages = [
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{"role": "system", "content": system_prompt},
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)
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# 5. Tokenize and Prepare for Generation
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device = model.device if hasattr(model, 'device') else ('cuda' if torch.cuda.is_available() else 'cpu')
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inputs = tokenizer([text_input], return_tensors="pt").to(device)
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