Instructions to use sivan22/halacha-siman-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sivan22/halacha-siman-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sivan22/halacha-siman-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sivan22/halacha-siman-classifier") model = AutoModelForSequenceClassification.from_pretrained("sivan22/halacha-siman-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from sivan22/halacha-siman-classifier: direct link, hf CLI and curl.
- Browser
- Download file 740 MB
-
https://huggingface.co/sivan22/halacha-siman-classifier/resolve/main/model.safetensors
- Command line
-
hf download hf://sivan22/halacha-siman-classifier/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/sivan22/halacha-siman-classifier/resolve/main/model.safetensors
740 MB
- Xet hash:
- d83df92dc8e3d1c6db311bebb18a431297615b7614bb5ae35ac60137fea193c1
- Size of remote file:
- 740 MB
- SHA256:
- 5435ee0e1384f0a919a2205cfef31c22b8b74f56eb2443c5ad7a16a49e3b95f1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.