Instructions to use M47Labs/it_iptc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M47Labs/it_iptc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="M47Labs/it_iptc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("M47Labs/it_iptc") model = AutoModelForSequenceClassification.from_pretrained("M47Labs/it_iptc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49fc60e573d9e8fa2f522fc85c44b33570e380a75505c5a1c2ba863291bd8e80
- Size of remote file:
- 443 MB
- SHA256:
- de81d4de6392121583b9d25a6830287c1e47ffa665ba125d9695e54b8520ae35
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