Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use jordyvl/test_implementation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jordyvl/test_implementation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jordyvl/test_implementation")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jordyvl/test_implementation") model = AutoModelForSequenceClassification.from_pretrained("jordyvl/test_implementation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8c97d561ba9669ae9c4f4640fa80a03f08b9e5c24a1a4210c7e3a5ace8a3370
- Size of remote file:
- 4.34 kB
- SHA256:
- c7bd9bac697066f0791752e3c15187b1dfaa5a6c8c37b9941e29b53151f99bcf
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