Text Classification
Transformers
PyTorch
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use franfj/DIPROMATS_subtask_1_base_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use franfj/DIPROMATS_subtask_1_base_train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="franfj/DIPROMATS_subtask_1_base_train")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("franfj/DIPROMATS_subtask_1_base_train") model = AutoModelForSequenceClassification.from_pretrained("franfj/DIPROMATS_subtask_1_base_train") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c20862941a2856b0f6a14ff0e7095b97c24a33aa01b098e15a41494c77ea152
- Size of remote file:
- 1.11 GB
- SHA256:
- 5e7ab3b25351ef7ece166ea4908aa8198d4a0c3dce72788bd890014a8b3bb742
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