Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Sandrro/nspb_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sandrro/nspb_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sandrro/nspb_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sandrro/nspb_classifier") model = AutoModelForSequenceClassification.from_pretrained("Sandrro/nspb_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Sandrro/nspb_classifier: direct link, hf CLI and curl.
- Browser
- Download file 117 MB
-
https://huggingface.co/Sandrro/nspb_classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Sandrro/nspb_classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sandrro/nspb_classifier/resolve/main/pytorch_model.bin
117 MB
- Xet hash:
- c2695f351d594bd3b53d868ef17566a76c5891c0aa911ee554373e054d4e761b
- Size of remote file:
- 117 MB
- SHA256:
- db271f752206ee0a557374e0a579a0e8753a3dbccb54df62ad12505eb669edaa
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