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Draconis-Qwen3_Math-4B-PreviewPrithivMLmods
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4B Params BF16 Open Weights Inference Available

Draconis-Qwen3_Math-4B-Preview, developed by prithivMLmods, is a 4 billion parameter model fine-tuned on the Qwen3-4B architecture with a 40960 token context length. It is specifically optimized for mathematical reasoning, logical problem-solving, and structured content generation, excelling in STEM learning and technical applications. This model prioritizes precision, step-by-step reasoning, and efficient inference, making it suitable for resource-constrained environments requiring reliable mathematical and logical outputs.

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Parameters:4BContext length:32kArchitecture:TransformerPrecision:BF16Quantized variants:AvailableLast updated:May 2025
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prithivMLmods/Draconis-Qwen3_Math-4B-Preview
Popular Sampler Settings

Most commonly used values from Featherless users

temperature

This setting influences the sampling randomness. Lower values make the model more deterministic; higher values introduce randomness. Zero is greedy sampling.

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top_p

This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.

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top_k

This limits the number of top tokens to consider. Set to -1 to consider all tokens.

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frequency_penalty

This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.

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presence_penalty

This setting penalizes new tokens based on their presence in the generated text so far. Values > 0 encourage new tokens; < 0 encourages repetition.

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repetition_penalty

This setting penalizes new tokens based on their appearance in the prompt and generated text. Values > 1 encourage new tokens; < 1 encourages repetition.

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min_p

This setting representing the minimum probability for a token to be considered relative to the most likely token. Must be in [0, 1]. Set to 0 to disable.

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