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--- |
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license: apache-2.0 |
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base_model: coderop12/gemma2b-nirf-lookup-2025 |
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tags: |
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- gguf |
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- quantized |
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- gemma |
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- nirf |
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- education |
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- ranking |
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- indian-universities |
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- text-generation |
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library_name: gguf |
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model_name: gemma2b-nirf-lookup-gguf |
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inference: false |
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model_creator: coderop12 |
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model_type: gemma |
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quantization: f16 |
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language: |
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- en |
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pipeline_tag: text-generation |
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widget: |
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- text: "What is NIRF ranking methodology?" |
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example_title: "NIRF Methodology" |
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- text: "Which are the top engineering colleges in NIRF 2024?" |
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example_title: "Top Engineering Colleges" |
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- text: "How are universities ranked in India?" |
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example_title: "University Rankings" |
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--- |
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# gemma2b-nirf-lookup-gguf |
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This is a GGUF conversion of [coderop12/gemma2b-nirf-lookup-2025](https://huggingface.co/coderop12/gemma2b-nirf-lookup-2025). |
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## Model Details |
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- **Original Model**: coderop12/gemma2b-nirf-lookup-2025 |
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- **Format**: GGUF (F16 precision) |
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- **File Size**: ~4.9 GB |
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- **Architecture**: Gemma 2B |
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- **Specialization**: NIRF (National Institutional Ranking Framework) lookup and ranking queries |
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## Usage |
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### With llama.cpp |
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```bash |
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./llama-cli -m gemma2b-nirf-lookup-gguf.gguf -p "What is the NIRF ranking methodology?" |
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``` |
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### With Python (llama-cpp-python) |
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```python |
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from llama_cpp import Llama |
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llm = Llama(model_path="gemma2b-nirf-lookup-gguf.gguf") |
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response = llm("What are the top NIRF ranked engineering colleges?") |
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print(response['choices'][0]['text']) |
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``` |
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### With Ollama |
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```bash |
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# First, create a Modelfile |
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echo 'FROM ./gemma2b-nirf-lookup-gguf.gguf' > Modelfile |
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ollama create gemma2b-nirf-lookup-gguf -f Modelfile |
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ollama run gemma2b-nirf-lookup-gguf "Explain NIRF ranking parameters" |
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``` |
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## Model Capabilities |
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This model is specifically fine-tuned for: |
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- NIRF ranking information and queries |
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- Indian higher education institutional data |
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- University and college ranking explanations |
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- Educational policy and framework questions |
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## Technical Details |
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- **Quantization**: F16 (16-bit floating point) |
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- **Context Length**: 2048 tokens |
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- **License**: Follow original model license terms |
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- **Converted using**: llama.cpp conversion tools |
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## Original Model License |
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Please refer to the original model repository for license information. |
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