---
license: apache-2.0
base_model: coderop12/gemma2b-nirf-lookup-2025
tags:
- gguf
- quantized
- gemma
- nirf
- education
- ranking
- indian-universities
- text-generation
library_name: gguf
model_name: gemma2b-nirf-lookup-gguf
inference: false
model_creator: coderop12
model_type: gemma
quantization: f16
language:
- en
pipeline_tag: text-generation
widget:
- text: "What is NIRF ranking methodology?"
  example_title: "NIRF Methodology"
- text: "Which are the top engineering colleges in NIRF 2024?"
  example_title: "Top Engineering Colleges"
- text: "How are universities ranked in India?"
  example_title: "University Rankings"
---

# gemma2b-nirf-lookup-gguf

This is a GGUF conversion of [coderop12/gemma2b-nirf-lookup-2025](https://huggingface.co/coderop12/gemma2b-nirf-lookup-2025).

## Model Details
- **Original Model**: coderop12/gemma2b-nirf-lookup-2025
- **Format**: GGUF (F16 precision)
- **File Size**: ~4.9 GB
- **Architecture**: Gemma 2B
- **Specialization**: NIRF (National Institutional Ranking Framework) lookup and ranking queries

## Usage

### With llama.cpp
```bash
./llama-cli -m gemma2b-nirf-lookup-gguf.gguf -p "What is the NIRF ranking methodology?"
```

### With Python (llama-cpp-python)
```python
from llama_cpp import Llama

llm = Llama(model_path="gemma2b-nirf-lookup-gguf.gguf")
response = llm("What are the top NIRF ranked engineering colleges?")
print(response['choices'][0]['text'])
```

### With Ollama
```bash
# First, create a Modelfile
echo 'FROM ./gemma2b-nirf-lookup-gguf.gguf' > Modelfile
ollama create gemma2b-nirf-lookup-gguf -f Modelfile
ollama run gemma2b-nirf-lookup-gguf "Explain NIRF ranking parameters"
```

## Model Capabilities
This model is specifically fine-tuned for:
- NIRF ranking information and queries
- Indian higher education institutional data
- University and college ranking explanations
- Educational policy and framework questions

## Technical Details
- **Quantization**: F16 (16-bit floating point)
- **Context Length**: 2048 tokens
- **License**: Follow original model license terms
- **Converted using**: llama.cpp conversion tools

## Original Model License
Please refer to the original model repository for license information.