Instructions to use rcds/distilbert-SBD-it-judgements with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rcds/distilbert-SBD-it-judgements with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rcds/distilbert-SBD-it-judgements")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rcds/distilbert-SBD-it-judgements") model = AutoModelForTokenClassification.from_pretrained("rcds/distilbert-SBD-it-judgements", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from rcds/distilbert-SBD-it-judgements: direct link, hf CLI and curl.
- Browser
- Download file 539 MB
-
https://huggingface.co/rcds/distilbert-SBD-it-judgements/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rcds/distilbert-SBD-it-judgements/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rcds/distilbert-SBD-it-judgements/resolve/main/pytorch_model.bin
539 MB
- Xet hash:
- 36c3ef6b447020cc047a4fbdff1d7072defd87cf1fe4f838d48293c4ed111107
- Size of remote file:
- 539 MB
- SHA256:
- c62eefa294d532987a5b692bf21fa68fd48bd837d237e6467fcfe529ed9af917
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