Kazuki1450/Qwen3-0.6B_csum_6_10_clean_1p0_0p0_1p0_grpo_42_rule is an 0.8 billion parameter language model fine-tuned from Qwen/Qwen3-0.6B. This model was trained using the GRPO method, as introduced in the DeepSeekMath paper, which focuses on enhancing mathematical reasoning. It is suitable for tasks requiring improved reasoning capabilities, particularly in mathematical contexts, building upon the Qwen3 architecture.
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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.
top_p
This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.
top_k
This limits the number of top tokens to consider. Set to -1 to consider all tokens.
frequency_penalty
This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.
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.
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.
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.