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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("franfj/DIPROMATS_subtask_1") model = AutoModelForSequenceClassification.from_pretrained("franfj/DIPROMATS_subtask_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#2)
Verified signature- Adding `safetensors` variant of this model (f601b2385594a36ff4a5807e1d41e20b7883f580) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>8d5876d
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Librarian Bot: Add base_model information to model (#1)
- Librarian Bot: Add base_model information to model (0cbb8cf90433e874aa490f177a6c4c4d7488a8d1) Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>35b6080
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End of training
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Training in progress, epoch 1
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initial commit
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