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--- |
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license: apache-2.0 |
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inference: false |
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base_model: llmware/slim-q-gen |
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base_model_relation: quantized |
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tags: [green, p1, llmware-fx, ov, emerald] |
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--- |
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# slim-q-gen-tiny-ov |
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**slim-q-gen-tiny-ov** is a specialized function calling model that implements a generative 'question' (e.g., 'q-gen') function, which takes a context passage as an input, and then generates as an output a python dictionary consisting of one key: |
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`{'question': ['What was the amount of revenue in the quarter?']} ` |
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The model has been designed to accept one of three different parameters to guide the type of question-answer created: 'question' (generates a standard question), 'boolean' (generates a 'yes-no' question), and 'multiple choice' (generates a multiple choice question). |
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This is an OpenVino int4 quantized version of slim-q-gen, providing a very fast, very small inference implementation, optimized for AI PCs using Intel GPU, CPU and NPU. |
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### Model Description |
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- **Developed by:** llmware |
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- **Model type:** tinyllama |
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- **Parameters:** 1.1 billion |
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- **Model Parent:** llmware/slim-q-gen |
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- **Language(s) (NLP):** English |
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- **License:** Apache 2.0 |
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- **Uses:** Question generation from a context passage |
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- **RAG Benchmark Accuracy Score:** NA |
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- **Quantization:** int4 |
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## Model Card Contact |
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[llmware on github](https://www.github.com/llmware-ai/llmware) |
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[llmware on hf](https://www.huggingface.co/llmware) |
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[llmware website](https://www.llmware.ai) |
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