Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use HAriGa/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HAriGa/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HAriGa/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HAriGa/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("HAriGa/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec4a50c6e359e491b3ed89340c8d1341b8dc3a2babfedcdab154e5a1608d1296
- Size of remote file:
- 436 MB
- SHA256:
- 0c0180ebc90422ac1d64edb82be444837c0ffc2cc6635bf178c2d607ea58d76a
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