abeja/ABEJA-QwQ32b-Reasoning-Japanese-v1.0
ABEJA-QwQ32b-Reasoning-Japanese-v1.0 is a 32.8 billion parameter Japanese reasoning model developed by ABEJA. It is based on abeja/ABEJA-Qwen2.5-32b-Japanese-v0.1, which itself is a Qwen2.5-32B-Instruct model continuously pre-trained with a focus on Japanese. This model integrates the ChatVector from Qwen/QwQ-32B and undergoes additional training to enhance its Japanese reasoning capabilities, specifically designed to output a final answer after an explicit thought process enclosed in <think></think> tags.
Hugging Face 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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