Kazuki1450/Qwen3-1.7B-Base_geo_3_6_clean_1p0_0p0_1p0_grpo_42_rule is a 2 billion parameter language model, fine-tuned by Kazuki1450 from the Qwen3-1.7B-Base architecture. This model leverages the GRPO method, as introduced in the DeepSeekMath paper, to enhance its reasoning capabilities. With a context length of 32768 tokens, it is specifically optimized for tasks requiring advanced mathematical and logical reasoning. Its training methodology suggests a focus on improving the accuracy and depth of its analytical outputs.
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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.