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
File size: 135 Bytes
9f502c5 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:373b77f5262c3298b803303d49ea38949d3e92f08dc3bbb90b03f490413adae9
size 1345834856
|