Sentence Similarity
sentence-transformers
PyTorch
German
bert
Eval Results (legacy)
text-embeddings-inference
Instructions to use and-effect/musterdatenkatalog_clf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use and-effect/musterdatenkatalog_clf with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("and-effect/musterdatenkatalog_clf") sentences = [ "Bebauungspläne, vorhabenbezogene Bebauungspläne (Geltungsbereiche)", "Fachkräfte für Glücksspielsuchtprävention und -beratung", "Tagespflege Altenhilfe", "Bebauungsplan der Innenentwicklung gem. § 13a BauGB - Ortskern Rütenbrock" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert
This new file is equivalent to pytorch_model.bin but safe in the sense that
no arbitrary code can be put into it.
These files also happen to load much faster than their pytorch counterpart:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb
The widgets on your model page will run using this model even if this is not merged
making sure the file actually works.
If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions
Feel free to ignore this PR.