Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use cartesinus/fedcsis-intent_baseline-xlm_r-all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cartesinus/fedcsis-intent_baseline-xlm_r-all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cartesinus/fedcsis-intent_baseline-xlm_r-all")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cartesinus/fedcsis-intent_baseline-xlm_r-all") model = AutoModelForSequenceClassification.from_pretrained("cartesinus/fedcsis-intent_baseline-xlm_r-all") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 343e7c7edc22a6678773932bfc580195ce1dd45e93415f821d8af1c0bd7f203b
- Size of remote file:
- 1.11 GB
- SHA256:
- cec7180876a8353b174dd74929d936518e3973a38d5ec5070b810eabe154cf75
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