Sentence Similarity
sentence-transformers
Safetensors
multilingual
qwen3
feature-extraction
dense
custom_code
text-embeddings-inference
Instructions to use mykor/pplx-embed-v1-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mykor/pplx-embed-v1-4b with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mykor/pplx-embed-v1-4b", trust_remote_code=True) sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97c969cd64eb461acbb044cf0d9f8bdb98e6c26c034d63aedefe966342da6365
- Size of remote file:
- 11.4 MB
- SHA256:
- db3914d7cce5125c42bbbf875116cef2697023ba144bda8264ad1368595dde2b
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