How to use sugiv/modernbert-us-stablecoin-encoder with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sugiv/modernbert-us-stablecoin-encoder", dtype="auto")
How to use sugiv/modernbert-us-stablecoin-encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sugiv/modernbert-us-stablecoin-encoder") 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]
How to use sugiv/modernbert-us-stablecoin-encoder with PEFT:
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