Instructions to use simonschoe/TransformationTransformer3D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonschoe/TransformationTransformer3D with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="simonschoe/TransformationTransformer3D")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("simonschoe/TransformationTransformer3D") model = AutoModelForSequenceClassification.from_pretrained("simonschoe/TransformationTransformer3D", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e9aa3762b38dd63e36c1d33f2961718a8a2336bec72430459cb9428ed4008bc2
- Size of remote file:
- 499 MB
- SHA256:
- 2a8f05e56b0a55f33a9b21ce911d7c110bd95aae0a88517e64eaa45ed9ce2d4c
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