Qwen/Qwen3-4B-Instruct-2507
Qwen/Qwen3-4B-Instruct-2507 is a 4.0 billion parameter instruction-tuned causal language model developed by Qwen, featuring a native context length of 262,144 tokens. This updated version of the Qwen3-4B non-thinking mode demonstrates significant improvements across general capabilities including instruction following, logical reasoning, mathematics, coding, and long-tail knowledge coverage in multiple languages. It excels in subjective and open-ended tasks, providing helpful responses and high-quality text generation, making it suitable for diverse conversational AI and agentic applications.
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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.
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.
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.