Instructions to use KAlex13/policy_title with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KAlex13/policy_title with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KAlex13/policy_title")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KAlex13/policy_title") model = AutoModelForSequenceClassification.from_pretrained("KAlex13/policy_title", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45aa28dedd68e73674bf04e9907c32549d06bdaf76e627222b81d683461c9696
- Size of remote file:
- 409 MB
- SHA256:
- 12544b69f46b33365bebaa46ae0419d300f6eb7e0e2a3ec5f15bcdf1270f1787
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.