recursal/RWKV6QwQ-32B-final-250307
The recursal/RWKV6QwQ-32B-final-250307 is a 32 billion parameter RWKV-variant language model developed by recursal, based on the Qwen 2.5 QwQ 32B architecture. This model leverages linear attention to significantly reduce computational costs and improve inference efficiency, particularly for long context lengths. It demonstrates competitive performance across various benchmarks, including ARC Challenge and Winogrande, making it suitable for general language understanding and generation tasks where cost-effective inference is critical.
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.
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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.
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frequency_penalty
This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.
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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.
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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.
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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.
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