Instructions to use hadrakey/ai-facturing_multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hadrakey/ai-facturing_multi with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hadrakey/ai-facturing_multi") 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 hadrakey/ai-facturing_multi with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("hadrakey/ai-facturing_multi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4cf0b8a4846e6fad38daa452c0f12f97173016d8410822ce01c89246b690f26
- Size of remote file:
- 1.11 GB
- SHA256:
- b4e94ff87bd6198ee7e14ef7c2bc72603e261ad7ea6dcf1c81fcaa3dd5d240c1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.