---
license: gemma
library_name: transformers
pipeline_tag: image-text-to-text
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: To access Gemma on Hugging Face, you’re required to review and
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  Face and click below. Requests are processed immediately.
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base_model: google/gemma-3-27b-pt
---

# Model Card for Dhruv-27b-preview

---

## Model Overview

Dhruv-27B-preview is a powerful 27-billion parameter language model based on **Gemma3**, fine-tuned for advanced reasoning tasks. Dhruv-27B is part of the Gemini Reasoning Series, optimized for high performance on academic, logical, and factual evaluations. It is capable of deep contextual reasoning and chain-of-thought generation, making it suitable for research, enterprise applications, and AI agents requiring robust general knowledge understanding.

---

## Key Metrics

Dhruv-27b-preview achieves strong performance on key benchmarks:

```
+------------------------+--------+
|        Metric         | Score  |
+------------------------+--------+
| MMLU (5-shot)          | 80.0%  |
| GPQA (0-shot)          | 52.0%  |
+------------------------+--------+
```

---

## Model Architecture

- **Base Model**: Gemma3
- **Model Size**: 27B parameters
- **Type**: Decoder-only Transformer (causal LM)
- **Precision**: bf16 with int8 quantization for inference efficiency
- **Training Objective**: Instruction-tuned with emphasis on reasoning, question answering, and factual correctness

---

## Intended Use

- **Research and academic QA tasks**
- **General-purpose reasoning agents**
- **Multilingual factual reasoning**
- **Enterprise AI tools requiring high factual accuracy and depth**

---

## USAGE
- **Use a System Template**
---

## Limitations

- Not optimized for creative generation or dialog tasks.
- May hallucinate in areas with limited training data.
- Requires fine-grained prompt engineering for complex instructions.

---

## Citation

```bibtex
@misc{vicharai_dhruv27b,
  title={Dhruv-27B: Gemma3 Reasoning Model},
  author={vicharai},
  year={2025},
  publisher={vicharai},
  url={https://vichar.io}
}
```
**Developed by vichar ai [Huggingface](https://huggingface.co/vicharai)  [Website](https://vichar.io)**