Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use P829692/thesis-model-2-original with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use P829692/thesis-model-2-original with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="P829692/thesis-model-2-original")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("P829692/thesis-model-2-original") model = AutoModelForSequenceClassification.from_pretrained("P829692/thesis-model-2-original") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2b730410abf1848b6db93306a501dcfb0dc6d6c38d270859c15caa8b08a2593
- Size of remote file:
- 438 MB
- SHA256:
- 300246da21f3b2fd7dcf379b617c8dae55478f42c5d4ed0985223e7dbad2d109
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