Featherless
QwQ-32B-ArliAI-RpR-v3ArliAI
Start Chat
32B Params FP8 Open Weights Inference Available

QwQ-32B-ArliAI-RpR-v3 by ArliAI is a 32-billion parameter model fine-tuned on the QwQ-32B base, specializing in roleplay and creative writing. It features a unique reasoning capability for long multi-turn chats, achieved through a custom RpR dataset and training methodology that prioritizes creativity and minimizes cross-context repetition. The model is designed to produce coherent and engaging outputs, making it suitable for complex narrative generation.

Loading preview...

Parameters:32BContext length:32kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:April 2025
0.0M
0.0K

Model tree for

ArliAI/QwQ-32B-ArliAI-RpR-v3
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.

1

top_p

This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.

1

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.

1

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.

–