Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Instructions to use mitra-mir/setfit_model_Ireland_binary_label2_epochs2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mitra-mir/setfit_model_Ireland_binary_label2_epochs2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mitra-mir/setfit_model_Ireland_binary_label2_epochs2") 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] - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mitra-mir/setfit_model_Ireland_binary_label2_epochs2: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/mitra-mir/setfit_model_Ireland_binary_label2_epochs2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mitra-mir/setfit_model_Ireland_binary_label2_epochs2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mitra-mir/setfit_model_Ireland_binary_label2_epochs2/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 6419806b4884f53869ccdebf116fe6ed0be7dec4f349c78ce70324a7f86c0018
- Size of remote file:
- 438 MB
- SHA256:
- c4816a7fe865b8ceb072f30c7f092c7ffc81dada5ee65c3c88672c6be1b6858a
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