Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use katzenbach/testMetaphor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use katzenbach/testMetaphor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="katzenbach/testMetaphor")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("katzenbach/testMetaphor") model = AutoModelForSequenceClassification.from_pretrained("katzenbach/testMetaphor") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b57cb1e9153f0a35080fe9bf4fd39734b7fbaf6b3793a47811b90b59b80cc7b2
- Size of remote file:
- 4.54 kB
- SHA256:
- 4ec9235911f63780df7b1b77e110dfc93f36d9fa19a286836d40dca6a4618188
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