Instructions to use ayanami-kitasan/code-pruner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ayanami-kitasan/code-pruner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ayanami-kitasan/code-pruner")# Load model directly from transformers import SwePrunerForCodeCompression model = SwePrunerForCodeCompression.from_pretrained("ayanami-kitasan/code-pruner", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -1
config.json
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{
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"architectures": [
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"
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"backbone_model_name_or_path": "Qwen/Qwen3-Reranker-0.6B",
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"bottleneck": 256,
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{
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"architectures": [
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"SwePrunerForCodeCompression"
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],
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"backbone_model_name_or_path": "Qwen/Qwen3-Reranker-0.6B",
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"bottleneck": 256,
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