Text Retrieval
Transformers
Safetensors
sentence-transformers
English
kpr-bert
feature-extraction
custom_code
Instructions to use knowledgeable-ai/kpr-bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use knowledgeable-ai/kpr-bert-base-uncased with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("knowledgeable-ai/kpr-bert-base-uncased", trust_remote_code=True, dtype="auto") - sentence-transformers
How to use knowledgeable-ai/kpr-bert-base-uncased with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("knowledgeable-ai/kpr-bert-base-uncased", 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:
- 7ce8a074424ea8633edd31b580c2af1a2cd81f0af110bd32c47c3ed7c36492e6
- Size of remote file:
- 11.1 GB
- SHA256:
- 7ac70ec87164d457b56b081b9022deff06cd8dd19d74ade2655fe5154e5ad52b
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