Qwen/Qwen3.5-397B-A17B
Qwen3.5-397B-A17B is a causal language model with a vision encoder developed by Qwen, featuring 397 billion total parameters with 17 billion activated. It utilizes an efficient hybrid architecture combining Gated Delta Networks and sparse Mixture-of-Experts for high-throughput inference. This model excels in unified vision-language understanding, agentic capabilities, and supports an extended context length of 262,144 tokens, extensible up to 1,010,000 tokens, making it suitable for complex multimodal tasks and ultra-long text processing across 201 languages.
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.
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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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