Text Classification
Transformers
PyTorch
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use franfj/DIPROMATS_subtask_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use franfj/DIPROMATS_subtask_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="franfj/DIPROMATS_subtask_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("franfj/DIPROMATS_subtask_1") model = AutoModelForSequenceClassification.from_pretrained("franfj/DIPROMATS_subtask_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07527a109fa5f008c40f26b21e9b8f950a342ad4920b4323ed350476a91b077f
- Size of remote file:
- 1.11 GB
- SHA256:
- b655cd429a8a6b86d01e7374f50bbc53f5c56fdd11a64b7a42b5285c44bf1c43
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