Qwen/Qwen3-Coder-30B-A3B-Instruct
Qwen/Qwen3-Coder-30B-A3B-Instruct is a 30.5 billion parameter (3.3 billion activated) causal language model developed by Qwen, featuring a Mixture-of-Experts (MoE) architecture with 128 experts. This model is specifically optimized for agentic coding, agentic browser-use, and foundational coding tasks, offering native support for a 262,144-token context length. It excels in tool calling capabilities and is designed for repository-scale code understanding.
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.
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