Instructions to use ingeol/dpr_facets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ingeol/dpr_facets with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ingeol/dpr_facets") 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 ingeol/dpr_facets with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ingeol/dpr_facets") model = AutoModel.from_pretrained("ingeol/dpr_facets", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a66f0630906893a03efa8f92395e3e43457ef305591918829339c9f29566433
- Size of remote file:
- 436 MB
- SHA256:
- 327ffea4fe0dccfbaf1911a4c8fd34fb343d721dda65e0c3f51cfbc01bc385fb
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