Instructions to use JohanHeinsen/PE_header_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use JohanHeinsen/PE_header_classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("JohanHeinsen/PE_header_classifier") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - setfit
How to use JohanHeinsen/PE_header_classifier with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("JohanHeinsen/PE_header_classifier") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from JohanHeinsen/PE_header_classifier: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/JohanHeinsen/PE_header_classifier/resolve/main/model.safetensors
- Command line
-
hf download hf://JohanHeinsen/PE_header_classifier/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/JohanHeinsen/PE_header_classifier/resolve/main/model.safetensors
438 MB
- Xet hash:
- 4326711c2817fc437f829d6bcc1af88459889e5adcbe867ab8361c3fffb3ed62
- Size of remote file:
- 438 MB
- SHA256:
- 1b7a0a1eed337603981cdccdfe244c2bb8af4e9e8a7a587a325db20fe200d86a
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