Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use osanseviero/example-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osanseviero/example-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="osanseviero/example-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("osanseviero/example-classifier") model = AutoModelForSequenceClassification.from_pretrained("osanseviero/example-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from osanseviero/example-classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/osanseviero/example-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://osanseviero/example-classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/osanseviero/example-classifier/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- c543f73e651097457b5e2c14a427028b8469b76f08345df335621bd17d7ffca3
- Size of remote file:
- 5.11 kB
- SHA256:
- 4a1d041c64e4b2c18212942fe9234dc1ab6521d03388b175441cef921a402110
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