Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use bowdpr/bowdpr_wiki_triviaft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bowdpr/bowdpr_wiki_triviaft with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bowdpr/bowdpr_wiki_triviaft") 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 bowdpr/bowdpr_wiki_triviaft with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("bowdpr/bowdpr_wiki_triviaft") model = AutoModel.from_pretrained("bowdpr/bowdpr_wiki_triviaft") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9c4260cc4a091f7c9ee7e68b7a298c61032cf7133499c7bb3b2ea4f9f236c7c
- Size of remote file:
- 438 MB
- SHA256:
- ab3f52aa7baaaa582b01b930196f51003d1a99e492f83bc19373d03b4c0bb74f
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