How to use minishlab/potion-base-8M with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("minishlab/potion-base-8M")
How to use minishlab/potion-base-8M with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("minishlab/potion-base-8M") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3]
95b90ee 3f12147 95b90ee 3f12147
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[ { "idx": 0, "name": "0", "path": ".", "type": "sentence_transformers.models.StaticEmbedding" }, { "idx": 1, "name": "1", "path": "1_Normalize", "type": "sentence_transformers.models.Normalize" } ]
