Skywork-SWE-32B is a 32.8 billion parameter code agent model developed by Skywork AI, specifically designed for software engineering (SWE) tasks. Built on the Qwen2.5-Coder-32B-Instruct backbone, it achieves 38.0% pass@1 accuracy on the SWE-bench Verified benchmark, outperforming previous open-source models in its class. With a notable context length of 131072 tokens, this model excels at automated code generation and bug fixing within comprehensive executable runtime environments. Its performance can further improve to 47.0% accuracy with test-time scaling techniques, making it suitable for complex software development workflows.
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Skywork/Skywork-SWE-32BMost 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.
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.
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.
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.