Instructions to use saroyehun/CAP_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saroyehun/CAP_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="saroyehun/CAP_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("saroyehun/CAP_classifier") model = AutoModelForSequenceClassification.from_pretrained("saroyehun/CAP_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from saroyehun/CAP_classifier: direct link, hf CLI and curl.
- Browser
- Download file 997 MB
-
https://huggingface.co/saroyehun/CAP_classifier/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://saroyehun/CAP_classifier@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/saroyehun/CAP_classifier/resolve/refs%2Fpr%2F1/optimizer.pt
997 MB
- Xet hash:
- 97815cb910a98e6cc8eed236b91689ee4fb064e25b6e9fe8fbbf6a2df4137147
- Size of remote file:
- 997 MB
- SHA256:
- 336c2ca3c85c661e4042e0bc54656b13cc53772aa6d5d1e47ba19bf14828394d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.