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+ ---
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+ license: other
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+ language:
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+ - en
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+ pipeline_tag: text-generation
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+ inference: false
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+ tags:
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+ - transformers
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+ - gguf
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+ - imatrix
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+ - SmallThinker-3B-Preview
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+ ---
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+ Quantizations of https://huggingface.co/PowerInfer/SmallThinker-3B-Preview
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+
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+ ### Inference Clients/UIs
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+ * [llama.cpp](https://github.com/ggerganov/llama.cpp)
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+ * [KoboldCPP](https://github.com/LostRuins/koboldcpp)
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+ * [ollama](https://github.com/ollama/ollama)
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+ * [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
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+ * [jan](https://github.com/janhq/jan)
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+ * [GPT4All](https://github.com/nomic-ai/gpt4all)
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+ ---
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+
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+ # From original readme
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+
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+ We introduce **SmallThinker-3B-preview**, a new model fine-tuned from the [Qwen2.5-3b-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) model.
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+
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+ Now you can directly deploy SmallThinker On your phones with [PowerServe](https://github.com/powerserve-project/PowerServe).
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+
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+ ## Benchmark Performance
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+
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+ | Model | AIME24 | AMC23 | GAOKAO2024_I | GAOKAO2024_II | MMLU_STEM | AMPS_Hard | math_comp |
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+ |---------|--------|-------|--------------|---------------|-----------|-----------|-----------|
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+ | Qwen2.5-3B-Instruct | 6.67 | 45 | 50 | 35.8 | 59.8 | - | - |
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+ | SmallThinker | 16.667 | 57.5 | 64.2 | 57.1 | 68.2 | 70 | 46.8 |
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+ | GPT-4o | 9.3 | - | - | - | 64.2 | 57 | 50 |
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+
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+ Limitation: Due to SmallThinker's current limitations in instruction following, for math_comp we adopt a more lenient evaluation method where only correct answers are required, without constraining responses to follow the specified AAAAA format.
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+
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+ Colab Link: [Colab](https://colab.research.google.com/drive/182q600at0sVw7uX0SXFp6bQI7pyjWXQ2?usp=sharing)
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+ ## Intended Use Cases
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+
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+ SmallThinker is designed for the following use cases:
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+
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+ 1. **Edge Deployment:** Its small size makes it ideal for deployment on resource-constrained devices.
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+ 2. **Draft Model for QwQ-32B-Preview:** SmallThinker can serve as a fast and efficient draft model for the larger QwQ-32B-Preview model. From my test, in llama.cpp we can get 70% speedup (from 40 tokens/s to 70 tokens/s).