Azure99/Blossom-V6.3-14B
Azure99/Blossom-V6.3-14B is a 14 billion parameter open-source conversational large language model developed by Azure99, built upon the Qwen3-14B-Base architecture. It features a 32768 token context length and is specifically designed to provide a cost-effective, locally accessible general-purpose model. This version improves upon previous iterations by addressing repeated-output issues and enhancing overall capabilities, making it suitable for a wide range of conversational AI applications.
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.
–
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.
–