Instructions to use satish860/sms_detection_algorithm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use satish860/sms_detection_algorithm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="satish860/sms_detection_algorithm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("satish860/sms_detection_algorithm") model = AutoModelForSequenceClassification.from_pretrained("satish860/sms_detection_algorithm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from satish860/sms_detection_algorithm: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/satish860/sms_detection_algorithm/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://satish860/sms_detection_algorithm/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/satish860/sms_detection_algorithm/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- ec50a0e002e69dff4775362b4e42c2b674aa8e7eae3c12d2e6b647d7c9834dee
- Size of remote file:
- 268 MB
- SHA256:
- 2056cd1dcb79806314b2965d85ec8262f8e889b389fb7fd48e0d4abdbb08da0f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.