Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use Loquats/test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Loquats/test1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Loquats/test1") 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 Loquats/test1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Loquats/test1") model = AutoModel.from_pretrained("Loquats/test1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3fdbb7267619f6d09110c42ce7a2a3f06dd294405ee9b17749df0af14e5e31a
- Size of remote file:
- 438 MB
- SHA256:
- f882bb35fcbc3c14bff4925f2fc6dc2574e18bd1a9e87bdaa5792b978548e574
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