Feature Extraction
sentence-transformers
ONNX
Safetensors
multilingual
bidirectional_pplx_qwen3
sentence-similarity
mteb
custom_code
text-embeddings-inference
Instructions to use LHC88/pplx-embed-v1-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use LHC88/pplx-embed-v1-4B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LHC88/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
Download model.safetensors from LHC88/pplx-embed-v1-4B: direct link, hf CLI and curl.
- Browser
- Download file 16.1 GB
-
https://huggingface.co/LHC88/pplx-embed-v1-4B/resolve/main/model.safetensors
- Command line
-
hf download hf://LHC88/pplx-embed-v1-4B/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/LHC88/pplx-embed-v1-4B/resolve/main/model.safetensors
16.1 GB
- Xet hash:
- e3e02486a8c934c7129a3a601fcf5176c4f49583340f671a6bb687fa96e4b22c
- Size of remote file:
- 16.1 GB
- SHA256:
- 35f5ccd0a3c772e1a580d10056c294a960e5f2ee7c12e6997171541fbabf4a09
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