Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use joniponi/facility-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joniponi/facility-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="joniponi/facility-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("joniponi/facility-classifier") model = AutoModelForSequenceClassification.from_pretrained("joniponi/facility-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from joniponi/facility-classifier: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/joniponi/facility-classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://joniponi/facility-classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/joniponi/facility-classifier/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 11deb75144bbd1d66df378de7e004f07768dd337d01db19aa249fc7cfefbedce
- Size of remote file:
- 268 MB
- SHA256:
- 0a202be53bbc0fc3204db8713e5d1748d9d65c5cce23e92da2bec967138dc898
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.