Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use dzinampini/api_endpoint_extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dzinampini/api_endpoint_extractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dzinampini/api_endpoint_extractor")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dzinampini/api_endpoint_extractor") model = AutoModelForSequenceClassification.from_pretrained("dzinampini/api_endpoint_extractor") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 816cc911e12f6ddff6a18241d8cccd031a915e26cd07a5e6436f0cbbc8b3213f
- Size of remote file:
- 268 MB
- SHA256:
- 01ad0f52185a465798bea8a43a5cef818a08317ad4137206448542610271e911
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