Instructions to use texturejc/texture-frames-frame with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use texturejc/texture-frames-frame with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="texturejc/texture-frames-frame")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("texturejc/texture-frames-frame", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d3943154cebb49c867e81536ef2d9f77d26d89bfd07b25993d079c1c7cabfcc
- Size of remote file:
- 1.75 GB
- SHA256:
- 0f8d6ec4ab5faca054926d249384896db60c41b8788d3f3480b9305dd17de0df
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