Text Classification
Transformers
PyTorch
English
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use PhucLe/LRO_v1.0.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PhucLe/LRO_v1.0.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PhucLe/LRO_v1.0.0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PhucLe/LRO_v1.0.0") model = AutoModelForSequenceClassification.from_pretrained("PhucLe/LRO_v1.0.0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6de2aed5917776b2917e1b8dea8f985420794107a38e16f67990fc4a9a1acffd
- Size of remote file:
- 1.34 GB
- SHA256:
- 883fd30d3ff4e8bad95094eff275791c70b62c963eba854bf689bd280386b821
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