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:
- 35ff75037d792e6973e1f43a7f64489644b7685244afab4f7fdc4f5317503f7d
- Size of remote file:
- 306 MB
- SHA256:
- b9e6bded234ea7be9250487f6e7ed26ccb3f04eb74443d78617d8328c3d3e41b
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