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qwen2.5_1.5b-gsm8k-test-step1000Ilia2003Mah
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1.5B Params BF16 Inference Available

The Ilia2003Mah/qwen2.5_1.5b-gsm8k-test-step1000 model is a 1.5 billion parameter language model, likely based on the Qwen2.5 architecture, developed by Ilia2003Mah. This model is specifically fine-tuned for mathematical reasoning tasks, indicated by its GSM8K dataset focus. Its primary strength lies in numerical problem-solving, making it suitable for applications requiring arithmetic and logical deduction.

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Parameters:1.5BContext length:32kArchitecture:TransformerPrecision:BF16Quantized variants:AvailableLast updated:March 2026
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Ilia2003Mah/qwen2.5_1.5b-gsm8k-test-step1000
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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