Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Sphere-Fall2022/nima-test-bert-glue with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sphere-Fall2022/nima-test-bert-glue with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sphere-Fall2022/nima-test-bert-glue")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sphere-Fall2022/nima-test-bert-glue") model = AutoModelForSequenceClassification.from_pretrained("Sphere-Fall2022/nima-test-bert-glue") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62aab6f8a654dfb79a5d6e459510af32c7dbec60779ec6a5cca64bf474bae074
- Size of remote file:
- 268 MB
- SHA256:
- d768fe0d67c6ac4ca0c516ff7789c4bc9c4c65b70d6f58ed8d48bef7d8d6eecd
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