Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use Neokun004/Testbge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Neokun004/Testbge with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Neokun004/Testbge") 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 Neokun004/Testbge with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Neokun004/Testbge") model = AutoModel.from_pretrained("Neokun004/Testbge", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae37b1aef955568e9a7873a9efc1160f8f75cfd34270330519596f3448db2344
- Size of remote file:
- 134 MB
- SHA256:
- ac7f3458ab10f89b5155e22e495200ee519e97009bec901a01e02c9b7b893932
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