cyberagent/DeepSeek-R1-Distill-Qwen-14B-Japanese
The cyberagent/DeepSeek-R1-Distill-Qwen-14B-Japanese is a 14 billion parameter language model, fine-tuned for Japanese language tasks. It is based on the DeepSeek-R1-Distill-Qwen-14B architecture, leveraging its reasoning capabilities. This model is specifically optimized for generating Japanese text and understanding Japanese queries, making it suitable for applications requiring high-quality Japanese language processing.
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.
–
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.
–