Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use azamat/mapper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use azamat/mapper with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("azamat/mapper") 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 azamat/mapper with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("azamat/mapper") model = AutoModel.from_pretrained("azamat/mapper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9701212b7d9696caa079d6eb2c48a946f940f06c0f0b8d4e9f1137886ada8d5d
- Size of remote file:
- 438 MB
- SHA256:
- 144f8c0537318547f248bc0665eb51779134a23c0770a76c157fcf263b43690d
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