Liontix/Qwen3-4B-Thinking-2507-Gemini-2.5-Pro-Distill is a 4 billion parameter language model fine-tuned by Liontix, based on the Qwen3-4B-Thinking-2507 variant. This model is specifically trained on a Gemini 2.5 Pro reasoning dataset, optimizing it for complex reasoning tasks. It excels in applications requiring logical problem-solving, such as coding, mathematics, and intricate logical questions, leveraging its 40960 token context length.
Loading preview...
Model tree for
Liontix/Qwen3-4B-Thinking-2507-Gemini-2.5-Pro-DistillMost 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.