JungZoona/T3Q-qwen2.5-14b-v1.0-e3 is a 14.8 billion parameter language model, post-trained from Qwen/Qwen2.5-14B-Instruct-1M. Developed by JungZoona, this model achieved 1st place in performance among models under 32B parameters on the Global Open LLM Leaderboard. It is optimized for general instruction-following tasks, demonstrating strong performance metrics for its size.
Loading preview...
Model tree for
JungZoona/T3Q-qwen2.5-14b-v1.0-e3Most 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.