Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use katzenbach/testMetaphor3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use katzenbach/testMetaphor3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="katzenbach/testMetaphor3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("katzenbach/testMetaphor3") model = AutoModelForSequenceClassification.from_pretrained("katzenbach/testMetaphor3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb17907a2992cd2fed3c7eeedb96d58e9dcc34360a04fa7ef2a27c57def61976
- Size of remote file:
- 4.54 kB
- SHA256:
- adace05ff0a3cd3b0d555576e9f9399bbafe1b0b73a7740f76ec6d50f8bfcb99
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