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  ---
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  ## ***See [our collection](https://huggingface.co/collections/unsloth/deepseek-r1-all-versions-678e1c48f5d2fce87892ace5) for versions of Deepseek-R1 including GGUF and original formats.***
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-
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  ### Instructions to run this model in llama.cpp:
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  Or you can view more detailed instructions here: [unsloth.ai/blog/deepseek-r1](https://unsloth.ai/blog/deepseek-r1)
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  1. Do not forget about `<|User|>` and `<|Assistant|>` tokens! - Or use a chat template formatter
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- 2. Example with K & V quantized cache **Notice -no-cnv disables auto conversation mode**
 
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  ```bash
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  ./llama.cpp/llama-cli \
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- --model unsloth/DeepSeek-R1-Distill-Qwen-1.5B-GGUF/DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M.gguf \
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  --cache-type-k q8_0 \
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- --cache-type-v q8_0 \
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  --threads 16 \
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  --prompt '<|User|>What is 1+1?<|Assistant|>' \
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  -no-cnv
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  ```
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  Example output:
 
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  ```txt
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- The sum of 1 and 1 is **2**. Here's a simple step-by-step breakdown:
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-
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- 1. **Start with the number 1.**
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- 2. **Add another 1 to it.**
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- 3. **The result is 2.**
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-
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- So, **1 + 1 = 2**. [end of text]
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- ```
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  4. If you have a GPU (RTX 4090 for example) with 24GB, you can offload multiple layers to the GPU for faster processing. If you have multiple GPUs, you can probably offload more layers.
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  ```bash
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  ./llama.cpp/llama-cli \
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- --model unsloth/DeepSeek-R1-Distill-Qwen-1.5B-GGUF/DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M.gguf
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  --cache-type-k q8_0
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- --cache-type-v q8_0
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  --threads 16
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  --prompt '<|User|>What is 1+1?<|Assistant|>'
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  --n-gpu-layers 20 \
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  -no-cnv
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  ```
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-
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  # Finetune LLMs 2-5x faster with 70% less memory via Unsloth!
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  We have a free Google Colab Tesla T4 notebook for Llama 3.1 (8B) here: https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_(8B)-Alpaca.ipynb
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  ---
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  ## ***See [our collection](https://huggingface.co/collections/unsloth/deepseek-r1-all-versions-678e1c48f5d2fce87892ace5) for versions of Deepseek-R1 including GGUF and original formats.***
 
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  ### Instructions to run this model in llama.cpp:
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  Or you can view more detailed instructions here: [unsloth.ai/blog/deepseek-r1](https://unsloth.ai/blog/deepseek-r1)
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  1. Do not forget about `<|User|>` and `<|Assistant|>` tokens! - Or use a chat template formatter
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+ 2. Obtain the latest `llama.cpp` at https://github.com/ggerganov/llama.cpp
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+ 3. Example with Q8_0 K quantized cache **Notice -no-cnv disables auto conversation mode**
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  ```bash
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  ./llama.cpp/llama-cli \
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+ --model unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF/DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf \
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  --cache-type-k q8_0 \
 
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  --threads 16 \
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  --prompt '<|User|>What is 1+1?<|Assistant|>' \
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  -no-cnv
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  ```
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  Example output:
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+
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  ```txt
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+ <think>
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+ Okay, so I need to figure out what 1 plus 1 is. Hmm, where do I even start? I remember from school that adding numbers is pretty basic, but I want to make sure I understand it properly.
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+ Let me think, 1 plus 1. So, I have one item and I add another one. Maybe like a apple plus another apple. If I have one apple and someone gives me another, I now have two apples. So, 1 plus 1 should be 2. That makes sense.
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+ Wait, but sometimes math can be tricky. Could it be something else? Like, in a different number system maybe? But I think the question is straightforward, using regular numbers, not like binary or hexadecimal or anything.
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+ I also recall that in arithmetic, addition is combining quantities. So, if you have two quantities of 1, combining them gives you a total of 2. Yeah, that seems right.
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+ Is there a scenario where 1 plus 1 wouldn't be 2? I can't think of any...
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+ ```
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+
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  4. If you have a GPU (RTX 4090 for example) with 24GB, you can offload multiple layers to the GPU for faster processing. If you have multiple GPUs, you can probably offload more layers.
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  ```bash
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  ./llama.cpp/llama-cli \
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+ --model unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF/DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf
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  --cache-type-k q8_0
 
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  --threads 16
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  --prompt '<|User|>What is 1+1?<|Assistant|>'
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  --n-gpu-layers 20 \
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  -no-cnv
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  ```
 
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  # Finetune LLMs 2-5x faster with 70% less memory via Unsloth!
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  We have a free Google Colab Tesla T4 notebook for Llama 3.1 (8B) here: https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_(8B)-Alpaca.ipynb
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