Instructions to use ilhkn/OFFICE_EXPENSES with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ilhkn/OFFICE_EXPENSES with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ilhkn/OFFICE_EXPENSES") 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 ilhkn/OFFICE_EXPENSES with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("ilhkn/OFFICE_EXPENSES") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ilhkn/OFFICE_EXPENSES: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/ilhkn/OFFICE_EXPENSES/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ilhkn/OFFICE_EXPENSES/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ilhkn/OFFICE_EXPENSES/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 3ca39f5176af8fcee9e564c273d476388e44af856ba0a3c628df383501384b46
- Size of remote file:
- 438 MB
- SHA256:
- 617ce13affb70717c34429728b40c22309ddd5105987ea881641c9d198b61598
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