Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use gemasphi/laprador_pt_pb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use gemasphi/laprador_pt_pb with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("gemasphi/laprador_pt_pb") 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 gemasphi/laprador_pt_pb with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("gemasphi/laprador_pt_pb") model = AutoModel.from_pretrained("gemasphi/laprador_pt_pb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gemasphi/laprador_pt_pb: direct link, hf CLI and curl.
- Browser
- Download file 266 MB
-
https://huggingface.co/gemasphi/laprador_pt_pb/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gemasphi/laprador_pt_pb/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gemasphi/laprador_pt_pb/resolve/main/pytorch_model.bin
266 MB
- Xet hash:
- 4298471d97b3d80ccfc1eef270e8133fd95613f681575f1a97d15e3334b23b39
- Size of remote file:
- 266 MB
- SHA256:
- 7cc0827c40f05f0b350970d1467948c0088d0855f037b5b026aaf3bbed634b2a
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