Instructions to use osanseviero/clip-st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use osanseviero/clip-st with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("osanseviero/clip-st") 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] - Notebooks
- Google Colab
- Kaggle
TODO: Name of Model
TODO: Description
Model Description
TODO: Add relevant content
(0) Base Transformer Type: DistilBertModel
(1) Pooling mean
(2) Dense 768x512
Usage (Sentence-Transformers)
Using this model becomes more convenient when you have sentence-transformers installed:
pip install -U sentence-transformers
Then you can use the model like this:
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence"]
model = SentenceTransformer(TODO)
embeddings = model.encode(sentences)
print(embeddings)
TODO: Training Procedure
TODO: Evaluation Results
TODO: Citing & Authors
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