Instructions to use MatteoFasulo/xlm-roberta-base_42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MatteoFasulo/xlm-roberta-base_42 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MatteoFasulo/xlm-roberta-base_42")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MatteoFasulo/xlm-roberta-base_42") model = AutoModelForSequenceClassification.from_pretrained("MatteoFasulo/xlm-roberta-base_42") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ec124740b8f83f696058b7ab806f7217b9d03876d528f0db4d2213f64122ad6
- Size of remote file:
- 5.3 kB
- SHA256:
- 45b7a83d9cb4b80eb8ac053dd09d3375d95c386bbdb548484f10cdb0ffd4fdaf
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