Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use jegormeister/setfit-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jegormeister/setfit-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jegormeister/setfit-model") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use jegormeister/setfit-model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jegormeister/setfit-model") model = AutoModel.from_pretrained("jegormeister/setfit-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29b47b58a14d5cc22cedde8fd389dc225b5bd4b8312b86c8340407f57ee1467f
- Size of remote file:
- 437 MB
- SHA256:
- 75c22613458fca0d329dbfd7bec9e1818a3d1869c01f7d059a6954c9ea427673
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