Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use cartesinus/fedcsis-intent_baseline-xlm_r-pl 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-pl 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-pl")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cartesinus/fedcsis-intent_baseline-xlm_r-pl") model = AutoModelForSequenceClassification.from_pretrained("cartesinus/fedcsis-intent_baseline-xlm_r-pl") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 919657d3b0844715e814cbb3de4e727ef558a55c7ef80475f3089746aa2cb53d
- Size of remote file:
- 17.1 MB
- SHA256:
- affcfb1f45c4b14a70a6589c3d153b430ed4309e5a6613a88dab64d5a923a5d6
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