Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use contemmcm/8ea310d3b0b47f0d7a4874f2acd8cd9f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use contemmcm/8ea310d3b0b47f0d7a4874f2acd8cd9f with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="contemmcm/8ea310d3b0b47f0d7a4874f2acd8cd9f")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("contemmcm/8ea310d3b0b47f0d7a4874f2acd8cd9f") model = AutoModelForSequenceClassification.from_pretrained("contemmcm/8ea310d3b0b47f0d7a4874f2acd8cd9f", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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