Instructions to use ghomasHudson/style_change_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghomasHudson/style_change_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ghomasHudson/style_change_detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ghomasHudson/style_change_detection") model = AutoModelForSequenceClassification.from_pretrained("ghomasHudson/style_change_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ghomasHudson/style_change_detection: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/ghomasHudson/style_change_detection/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ghomasHudson/style_change_detection/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ghomasHudson/style_change_detection/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 1fbe21d2af79538dd2a623c163b78a07288a1f8b9a2bccf3b30413c5e0094afa
- Size of remote file:
- 433 MB
- SHA256:
- e925f3000a5edb5e0f21e6fd67cfcbd71689458f88e90772616ab758c5daeac7
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