Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
deberta-v2
feature-extraction
text-embeddings-inference
Instructions to use xushijie/polyBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use xushijie/polyBERT with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("xushijie/polyBERT") sentences = [ "[*]CC[*]", "[*]COC[*]", "[*]CC(C)C[*]" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use xushijie/polyBERT with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("xushijie/polyBERT") model = AutoModel.from_pretrained("xushijie/polyBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd368230edcd242d96a1cea015e9e878334c01ca81ca52a0ad126af31d88cff4
- Size of remote file:
- 242 kB
- SHA256:
- 2285839ce5a54c35acd7a59c38e531c243a5c46476e1ba11080bf11d303618d5
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