Kazuki1450/Qwen3-0.6B_nseq_4_8_clean_1p0_0p0_1p0_grpo_42_rule is a fine-tuned 0.8 billion parameter language model based on the Qwen3-0.6B architecture. This model was trained using the TRL framework and incorporates the GRPO method, which is designed to enhance mathematical reasoning capabilities. It is specifically optimized for tasks requiring advanced mathematical problem-solving, leveraging techniques from the DeepSeekMath research. This model is suitable for applications where robust mathematical reasoning is a primary requirement.
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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.