Qwen3-Swallow-8B-CPT-v0.2 by tokyotech-llm is an 8 billion parameter bilingual Japanese-English large language model, part of the Qwen3-Swallow family. Developed through Continual Pre-Training (CPT), Supervised Fine-Tuning (SFT), and Reinforcement Learning with Verifiable Rewards (RLVR), it excels in Japanese language proficiency and Japanese-English translation. This model maintains strong performance in math and coding tasks, with enhanced reasoning capabilities, making it suitable for applications requiring robust bilingual and STEM-oriented understanding.
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tokyotech-llm/Qwen3-Swallow-8B-CPT-v0.2Most 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.