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@@ -12,7 +12,7 @@ tags:
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  - instruction-following
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  - text-generation
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  - merged_16bit
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- base_model: unsloth/Qwen3-14B
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  datasets:
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  - beetlware/arabic-reasoning-dataset-logic
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  ---
@@ -81,12 +81,7 @@ model = AutoModelForCausalLM.from_pretrained(
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  # Ensure the model is in evaluation mode for inference
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  model.eval()
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  ```
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- ### --- Example for Inference with Thinking Steps (if the model was trained to produce them) ---
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- ### Qwen3 models expect special tags for thinking <think>...</think>
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- ### To enable thinking mode during inference (if supported by the fine-tuned model):
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- ### You might need to craft the prompt to ask the model to think.
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- ### Unsloth-trained Qwen3 models often respond to enable_thinking in tokenizer.apply_chat_template.
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- ### For a merged model, its ability to show <think> depends on the training data.
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  ```python
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  user_prompt_with_thinking_request = "استخدم التفكير المنطقي خطوة بخطوة: إذا كان لدي 4 تفاحات والشجرة فيها 20 تفاحة، فكم تفاحة لدي إجمالاً؟" # "Use step-by-step logical thinking: If I have 4 apples and the tree has 20 apples, how many apples do I have in total?"
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  - instruction-following
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  - text-generation
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  - merged_16bit
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+ base_model: beetlware/Bee1reason-arabic-Qwen-14B
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  datasets:
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  - beetlware/arabic-reasoning-dataset-logic
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  ---
 
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  # Ensure the model is in evaluation mode for inference
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  model.eval()
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  ```
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+
 
 
 
 
 
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  ```python
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  user_prompt_with_thinking_request = "استخدم التفكير المنطقي خطوة بخطوة: إذا كان لدي 4 تفاحات والشجرة فيها 20 تفاحة، فكم تفاحة لدي إجمالاً؟" # "Use step-by-step logical thinking: If I have 4 apples and the tree has 20 apples, how many apples do I have in total?"
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