royallab/ZephRP-m7b

royallab/ZephRP-m7b is a 7 billion parameter Mistral-based language model, merging HuggingFaceH4/zephyr-7b-alpha with a PEFT adapter trained on the LimaRP dataset. This model is specifically designed for advanced roleplaying scenarios, combining Zephyr's instruction-following with LimaRP's stylistic elements and message length control. It excels at generating character-driven responses within a defined roleplaying chat format, offering granular control over response length.

Warm
Public
7B
FP8
8192
License: cc-by-nc-4.0
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.