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--- |
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license: mit |
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language: |
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- en |
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base_model: |
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- deepseek-ai/DeepSeek-R1 |
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pipeline_tag: text-generation |
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tags: |
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- deepseek-r1 |
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- gguf-connector |
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--- |
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# GGUF quantized version of **deepseek-r1** |
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### review |
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- no more error loading message: "unknown pre-tokenizer type: deepseek-r1-qwen" |
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- works fine for llama architecture |
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### run the model |
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use any gguf connector to interact with gguf file(s), i.e., [connector](https://pypi.org/project/gguf-connector/) |
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### reference |
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- base model: deepseek-ai/[DeepSeek-R1](https://huggingface.co/deepseek-ai/DeepSeek-R1) |
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- tool used for quantization: [cutter](https://pypi.org/project/gguf-cutter) |
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### citation |
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[DeepSeek-R1](https://arxiv.org/pdf/2501.12948) |
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### appendices: model evaluation (written by deekseek-ai) |
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#### deepseek-r1-evaluation |
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for all our (here refer to deekseek-ai) models, the maximum generation length is set to 32,768 tokens; for benchmarks requiring sampling, we use a temperature of $0.6$, a top-p value of $0.95$, and generate 64 responses per query to estimate pass@1. |
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| Category | Benchmark (Metric) | Claude-3.5-Sonnet-1022 | GPT-4o 0513 | DeepSeek V3 | OpenAI o1-mini | OpenAI o1-1217 | DeepSeek R1 | |
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|----------|-------------------|----------------------|------------|--------------|----------------|------------|--------------| |
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| | Architecture | - | - | MoE | - | - | MoE | |
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| | # Activated Params | - | - | 37B | - | - | 37B | |
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| | # Total Params | - | - | 671B | - | - | 671B | |
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| English | MMLU (Pass@1) | 88.3 | 87.2 | 88.5 | 85.2 | **91.8** | 90.8 | |
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| | MMLU-Redux (EM) | 88.9 | 88.0 | 89.1 | 86.7 | - | **92.9** | |
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| | MMLU-Pro (EM) | 78.0 | 72.6 | 75.9 | 80.3 | - | **84.0** | |
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| | DROP (3-shot F1) | 88.3 | 83.7 | 91.6 | 83.9 | 90.2 | **92.2** | |
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| | IF-Eval (Prompt Strict) | **86.5** | 84.3 | 86.1 | 84.8 | - | 83.3 | |
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| | GPQA-Diamond (Pass@1) | 65.0 | 49.9 | 59.1 | 60.0 | **75.7** | 71.5 | |
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| | SimpleQA (Correct) | 28.4 | 38.2 | 24.9 | 7.0 | **47.0** | 30.1 | |
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| | FRAMES (Acc.) | 72.5 | 80.5 | 73.3 | 76.9 | - | **82.5** | |
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| | AlpacaEval2.0 (LC-winrate) | 52.0 | 51.1 | 70.0 | 57.8 | - | **87.6** | |
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| | ArenaHard (GPT-4-1106) | 85.2 | 80.4 | 85.5 | 92.0 | - | **92.3** | |
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| Code | LiveCodeBench (Pass@1-COT) | 33.8 | 34.2 | - | 53.8 | 63.4 | **65.9** | |
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| | Codeforces (Percentile) | 20.3 | 23.6 | 58.7 | 93.4 | **96.6** | 96.3 | |
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| | Codeforces (Rating) | 717 | 759 | 1134 | 1820 | **2061** | 2029 | |
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| | SWE Verified (Resolved) | **50.8** | 38.8 | 42.0 | 41.6 | 48.9 | 49.2 | |
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| | Aider-Polyglot (Acc.) | 45.3 | 16.0 | 49.6 | 32.9 | **61.7** | 53.3 | |
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| Math | AIME 2024 (Pass@1) | 16.0 | 9.3 | 39.2 | 63.6 | 79.2 | **79.8** | |
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| | MATH-500 (Pass@1) | 78.3 | 74.6 | 90.2 | 90.0 | 96.4 | **97.3** | |
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| | CNMO 2024 (Pass@1) | 13.1 | 10.8 | 43.2 | 67.6 | - | **78.8** | |
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| Chinese | CLUEWSC (EM) | 85.4 | 87.9 | 90.9 | 89.9 | - | **92.8** | |
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| | C-Eval (EM) | 76.7 | 76.0 | 86.5 | 68.9 | - | **91.8** | |
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| | C-SimpleQA (Correct) | 55.4 | 58.7 | **68.0** | 40.3 | - | 63.7 | |
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#### distilled model evaluation |
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| Model | AIME 2024 pass@1 | AIME 2024 cons@64 | MATH-500 pass@1 | GPQA Diamond pass@1 | LiveCodeBench pass@1 | CodeForces rating | |
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|------------------------------------------|------------------|-------------------|-----------------|----------------------|----------------------|-------------------| |
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| GPT-4o-0513 | 9.3 | 13.4 | 74.6 | 49.9 | 32.9 | 759 | |
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| Claude-3.5-Sonnet-1022 | 16.0 | 26.7 | 78.3 | 65.0 | 38.9 | 717 | |
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| o1-mini | 63.6 | 80.0 | 90.0 | 60.0 | 53.8 | **1820** | |
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| QwQ-32B-Preview | 44.0 | 60.0 | 90.6 | 54.5 | 41.9 | 1316 | |
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| DeepSeek-R1-Distill-Qwen-1.5B | 28.9 | 52.7 | 83.9 | 33.8 | 16.9 | 954 | |
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| DeepSeek-R1-Distill-Qwen-7B | 55.5 | 83.3 | 92.8 | 49.1 | 37.6 | 1189 | |
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| DeepSeek-R1-Distill-Qwen-14B | 69.7 | 80.0 | 93.9 | 59.1 | 53.1 | 1481 | |
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| DeepSeek-R1-Distill-Qwen-32B | **72.6** | 83.3 | 94.3 | 62.1 | 57.2 | 1691 | |
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| DeepSeek-R1-Distill-Llama-8B | 50.4 | 80.0 | 89.1 | 49.0 | 39.6 | 1205 | |
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| DeepSeek-R1-Distill-Llama-70B | 70.0 | **86.7** | **94.5** | **65.2** | **57.5** | 1633 | |
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\* these two tables are directly quoted from deepseek-ai |
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