clip-st / README.md
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tags:
  - sentence-transformers
  - feature-extraction

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({example})
embeddings = model.encode(sentences)
print(embeddings)

TODO: Training Procedure

TODO: Evaluation Results

TODO: Citing & Authors