Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use HeHeYeast/bert_base_retriever with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HeHeYeast/bert_base_retriever with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HeHeYeast/bert_base_retriever") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use HeHeYeast/bert_base_retriever with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("HeHeYeast/bert_base_retriever") model = AutoModel.from_pretrained("HeHeYeast/bert_base_retriever", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cfc3ff98cf1aa433215dac89e57c1d698acc8d8a89c4d751eff81cba54b1c686
- Size of remote file:
- 438 MB
- SHA256:
- c543f944518bd3df3f3c1c78db4dba79a458dce2f9abbc23df37a9001adb4726
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