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:
- c189a5ba33ba8ee4dc0cbc49f22446c5b64fffaf70ecd407b63cf4da71c1e485
- Size of remote file:
- 3.64 kB
- SHA256:
- 5471a64d50b1a41313ac594373850e6a92b6e3e2b33d9a7264dde8dc638b74a4
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