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-v5-gpu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yagosys/cloudinit-embedding-v5-gpu with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yagosys/cloudinit-embedding-v5-gpu") sentences = [ "cloud-init", "bootstrapping a cloud server", "infrastructure as code (IaC)", "database replication settings" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ccffc003fd261302f5bb6f751bc5e735f95e17bcd6189b6ea5109868b197ec5f
- Size of remote file:
- 90.9 MB
- SHA256:
- 48a446748abc6b5b9d8f8c6a1d805e4e6dd6ab91a3d9d9ed6bf9770f112b976c
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