Feature Extraction
Transformers
PyTorch
Tagalog
bert
tagalog
dependency-parsing
contrastive-learning
syntax
low-resource
text-embeddings-inference
Instructions to use paulbontempo/bert-tagalog-dependency-cl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paulbontempo/bert-tagalog-dependency-cl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="paulbontempo/bert-tagalog-dependency-cl")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("paulbontempo/bert-tagalog-dependency-cl") model = AutoModel.from_pretrained("paulbontempo/bert-tagalog-dependency-cl") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78b9aff7883a13f0a701c1a71fde99008e2d1f38063fa875cd3f1cfd590e9bb3
- Size of remote file:
- 711 MB
- SHA256:
- ba2df1f38cb219e5f0a48efedcb3d3685265490d57ed8c78a977196914f1f647
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