Instructions to use gustavecortal/distilcamembert-cae-component with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gustavecortal/distilcamembert-cae-component with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gustavecortal/distilcamembert-cae-component")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gustavecortal/distilcamembert-cae-component") model = AutoModelForSequenceClassification.from_pretrained("gustavecortal/distilcamembert-cae-component", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gustavecortal/distilcamembert-cae-component: direct link, hf CLI and curl.
- Browser
- Download file 272 MB
-
https://huggingface.co/gustavecortal/distilcamembert-cae-component/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gustavecortal/distilcamembert-cae-component/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gustavecortal/distilcamembert-cae-component/resolve/main/pytorch_model.bin
272 MB
- Xet hash:
- 8d2a17fae882c83484a609f5986635fa3ce23d1b41eafa86d7466beaae5c966a
- Size of remote file:
- 272 MB
- SHA256:
- 5025a6f2df79eb0b2701ae63020a94f92e5dc6f24945bc48b7fe68d3a6cbd1d3
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