Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use apsys/crypto-mini-lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use apsys/crypto-mini-lm with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("apsys/crypto-mini-lm") 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 apsys/crypto-mini-lm with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("apsys/crypto-mini-lm") model = AutoModel.from_pretrained("apsys/crypto-mini-lm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84822557d4bb081be8c9cb7e6d5aa2c2e9e7dd3dd0ce3f10fff00f60d5ca4be3
- Size of remote file:
- 90.9 MB
- SHA256:
- 7d97eb2adc3c00937dac13ba388f1b4f78d5c5565bdbf0cfc96673c8c41d29d6
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