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README.md
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license: mit
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## Overview
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## Variants
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| No | Variant | Cortex CLI command |
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| 1 | [gguf](https://huggingface.co/cortexso/deepseek-r1-distill-qwen-1.5b/tree/main) | cortex run deepseek-r1-distill-qwen-1.5b |
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## Use it with Jan (UI)
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1. Install **Jan** using [Quickstart](https://jan.ai/docs/quickstart)
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2. Use in Jan model Hub:
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cortexso/deepseek-r1-distill-qwen-1.5b
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## Use it with Cortex (CLI)
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1. Install **Cortex** using [Quickstart](https://cortex.jan.ai/docs/quickstart)
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2. Run the model with command:
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cortex run deepseek-r1-distill-qwen-1.5b
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## Credits
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- **Author:**
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- **Converter:** [Homebrew](https://www.homebrew.ltd/)
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- **Original License:** [License](https://huggingface.co/
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---
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license: mit
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---
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## Overview
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**DeepSeek** developed and released the [DeepSeek R1 Distill Qwen 1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B) model, a distilled version of the Qwen 1.5B language model. It is fine-tuned for high-performance text generation and optimized for dialogue and information-seeking tasks. This model achieves a balance of efficiency and accuracy while maintaining a smaller footprint compared to the original Qwen 1.5B.
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The model is designed for applications in customer support, conversational AI, and research, prioritizing both helpfulness and safety.
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## Variants
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| No | Variant | Cortex CLI command |
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| --- | --- | --- |
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| 1 | [gguf](https://huggingface.co/cortexso/deepseek-r1-distill-qwen-1.5b/tree/main) | `cortex run deepseek-r1-distill-qwen-1.5b` |
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## Use it with Jan (UI)
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1. Install **Jan** using [Quickstart](https://jan.ai/docs/quickstart)
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2. Use in Jan model Hub:
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```text
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cortexso/deepseek-r1-distill-qwen-1.5b
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```
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## Use it with Cortex (CLI)
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1. Install **Cortex** using [Quickstart](https://cortex.jan.ai/docs/quickstart)
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2. Run the model with command:
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```bash
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cortex run deepseek-r1-distill-qwen-1.5b
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```
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## Credits
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- **Author:** DeepSeek
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- **Converter:** [Homebrew](https://www.homebrew.ltd/)
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- **Original License:** [License](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B#7-license)
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- **Papers:** [DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning](https://arxiv.org/html/2501.12948v1)
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