Instructions to use texturejc/texture-frames-de-frame with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use texturejc/texture-frames-de-frame with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="texturejc/texture-frames-de-frame")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("texturejc/texture-frames-de-frame", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
187f0db | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:ab550317a7cf5e754d847b3627c29171fac37a1a358a18a8c2f01d494e2f026b
size 1355721342
|