Zero-Shot Classification
Transformers
PyTorch
Safetensors
Italian
xlm-roberta
text-classification
tensorflow
Eval Results (legacy)
Instructions to use Jiva/xlm-roberta-large-it-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jiva/xlm-roberta-large-it-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="Jiva/xlm-roberta-large-it-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jiva/xlm-roberta-large-it-mnli") model = AutoModelForSequenceClassification.from_pretrained("Jiva/xlm-roberta-large-it-mnli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00a3d3c7078ab90535ae701bd43ee3ea47eb4a7597f3e86e5d143a14557db040
- Size of remote file:
- 2.24 GB
- SHA256:
- 4db27ff0ea43ef8cee78f2fd988af78b9da15c5020e2a43b418f5a90d80f9161
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