Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:37
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use yagosys/cloudinit-embedding-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yagosys/cloudinit-embedding-v3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yagosys/cloudinit-embedding-v3") sentences = [ "cloud-init", "network configuration", "bootstrapping with user data", "user data" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73430ed7260cdf8b11774300dad76c43841f25dffab04309860a05bc08c0168d
- Size of remote file:
- 90.9 MB
- SHA256:
- 74caa05c92139d68134e1db6b79c9519fb5f2c963bbf753f7cad666988c323d9
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