|  | --- | 
					
						
						|  | license: mit | 
					
						
						|  | --- | 
					
						
						|  |  | 
					
						
						|  | ## Overview | 
					
						
						|  |  | 
					
						
						|  | **DeepSeek** developed and released the **DeepSeek-R1** series, featuring multiple model sizes fine-tuned for high-performance text generation. These models are optimized for dialogue, reasoning, and information-seeking tasks, providing a balance of efficiency and accuracy while maintaining a smaller footprint compared to their original counterparts. | 
					
						
						|  |  | 
					
						
						|  | The DeepSeek-R1 models include distilled and full-scale variants of both **Qwen** and **Llama** architectures, catering to various applications such as customer support, conversational AI, research, and enterprise automation. | 
					
						
						|  |  | 
					
						
						|  | ## Variants | 
					
						
						|  |  | 
					
						
						|  | ### DeepSeek-R1 | 
					
						
						|  |  | 
					
						
						|  | | No | Variant                                                                                        | Branch | Cortex CLI command                          | | 
					
						
						|  | | -- | ---------------------------------------------------------------------------------------------- | ------- | ------------------------------------------ | | 
					
						
						|  | | 1  | [DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/cortexso/deepseek-r1/tree/1.5b)         | 1.5b    | `cortex run [WIP]` | | 
					
						
						|  | | 2  | [DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/cortexso/deepseek-r1/tree/7b)             | 7b      | `cortex run [WIP]`   | | 
					
						
						|  | | 3  | [DeepSeek-R1-Distill-Llama-8B](https://huggingface.co/cortexso/deepseek-r1/tree/8b)           | 8b      | `cortex run [WIP]`  | | 
					
						
						|  | | 4  | [DeepSeek-R1-Distill-Qwen-14B](https://huggingface.co/cortexso/deepseek-r1/tree/14b)           | 14b     | `cortex run [WIP]`  | | 
					
						
						|  | | 5  | [DeepSeek-R1-Distill-Qwen-32B](https://huggingface.co/cortexso/deepseek-r1/tree/32b)           | 32b     | `cortex run [WIP]`  | | 
					
						
						|  | | 6  | [DeepSeek-R1-Distill-Llama-70B](https://huggingface.co/cortexso/deepseek-r1/tree/70b)         | 70b     | `cortex run [WIP]` | | 
					
						
						|  |  | 
					
						
						|  | Each branch contains a default quantized version: | 
					
						
						|  | - **Qwen-1.5B:** q4-km | 
					
						
						|  | - **Qwen-7B:** q4-km | 
					
						
						|  | - **Llama-8B:** q4-km | 
					
						
						|  | - **Qwen-14B:** q4-km | 
					
						
						|  | - **Qwen-32B:** q4-km | 
					
						
						|  | - **Llama-70B:** q4-km | 
					
						
						|  |  | 
					
						
						|  | ## Use it with Jan (UI) | 
					
						
						|  |  | 
					
						
						|  | 1. Install **Jan** using [Quickstart](https://jan.ai/docs/quickstart) | 
					
						
						|  | 2. Use in Jan model Hub: | 
					
						
						|  | ```text | 
					
						
						|  | cortexso/deepseek-r1 [WIP] | 
					
						
						|  | cortexso/deepseek-r1 [WIP] | 
					
						
						|  | ``` | 
					
						
						|  |  | 
					
						
						|  | ## Use it with Cortex (CLI) | 
					
						
						|  |  | 
					
						
						|  | 1. Install **Cortex** using [Quickstart](https://cortex.jan.ai/docs/quickstart) | 
					
						
						|  | 2. Run the model with command: | 
					
						
						|  | ```bash | 
					
						
						|  | cortex run [WIP] | 
					
						
						|  | ``` | 
					
						
						|  | or | 
					
						
						|  | ```bash | 
					
						
						|  | cortex run [WIP] | 
					
						
						|  | ``` | 
					
						
						|  |  | 
					
						
						|  | ## Credits | 
					
						
						|  |  | 
					
						
						|  | - **Author:** DeepSeek | 
					
						
						|  | - **Converter:** [Homebrew](https://www.homebrew.ltd/) | 
					
						
						|  | - **Original License:** [License](https://huggingface.co/deepseek-ai/DeepSeek-R1#license) | 
					
						
						|  | - **Papers:** [DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning](https://arxiv.org/html/2501.12948v1) |