Sentence Similarity
sentence-transformers
PyTorch
Transformers
distilbert
feature-extraction
text-embeddings-inference
Instructions to use GPL/arguana-msmarco-distilbert-gpl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use GPL/arguana-msmarco-distilbert-gpl with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("GPL/arguana-msmarco-distilbert-gpl") 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 GPL/arguana-msmarco-distilbert-gpl with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("GPL/arguana-msmarco-distilbert-gpl") model = AutoModel.from_pretrained("GPL/arguana-msmarco-distilbert-gpl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65f9f7df73ae7f41c7afe224abdb9f29e97ab40b4030936bbe504d63e89bee50
- Size of remote file:
- 265 MB
- SHA256:
- cabd6518d60e8e0e8e2148eb96e136396313e7cbf66f4abb5427e9a076cfb748
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