This model is a fine-tuned version of Qwen2-3B, optimized for enhanced reasoning capabilities in English. It has been trained on a curated dataset to improve performance on tasks requiring logical inference, comprehension, and instruction following.

Intended Uses & Limitations

Direct Use

Applications:
- Logical reasoning tasks
- Instruction-based question answering
- Conversational agents requiring enhanced reasoning

Downstream Use

Potential Applications:
- Integration into AI systems requiring reasoning capabilities
- Further fine-tuning for domain-specific tasks

Out-of-Scope Use

Not Recommended For:
- Tasks requiring real-time decision-making in critical systems
- Applications involving sensitive or personal data without proper safeguards

Bias, Risks, and Limitations

While efforts have been made to reduce biases during fine-tuning, the model may still exhibit biases present in the training data. Users should be cautious and evaluate the model's outputs, especially in sensitive applications.

How to Use

python

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="CALISTA-INDUSTRY/qwen_2_3B_reasoning_en_ft_v1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

rizkysulaeman/qwen_2_3B_reasoning_en_ft_v1

Model Card for CALISTA-INDUSTRY/qwen_2_3B_reasoning_en_ft_v1

Model Details

Model Description