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:
- 2e34e068271954ef84e234064e3899ad910268a329ab1528c3112051a3a802b4
- Size of remote file:
- 3.64 kB
- SHA256:
- 3b46ec93a38e8eb7433742ef5111c78af1598adb1e580342ce546d89f9827767
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