How to use TatvaRA/clip-skin-embeddings-finetuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("TatvaRA/clip-skin-embeddings-finetuned") sentences = [ "The image depicts multiple small, soft, flesh-colored to slightly hyperpigmented skin lesions located on the eyelid and surrounding skin. These lesions are pedunculated with a smooth surface, typical of skin tags (acrochordons). Some are more prominent and raised, while others are flatter against the skin surface. The surrounding skin appears slightly wrinkled, consistent with normal aging changes.", "The image shows a reticulated, net-like pattern of erythema and hyperpigmentation on the lower back. The lesions appear to be brownish-red in color with defined, irregular borders. There is no evidence of blistering or active inflammation. The distribution is linear and symmetric, suggesting exposure to a patterned heat source.", "The image shows a right lower leg with marked erythema covering most of the calf and extending around the ankle. The redness has an ill-defined border and there is noticeable swelling. The skin appears smooth and shiny, suggesting edema. There is no evidence of open wounds or pus. The distribution of redness and swelling is primarily around the shin and calf areas.", "The image displays toenails with signs of fungal infection. The nails appear thickened and discolored, predominantly yellowish-brown. There is noticeable onycholysis, especially in the larger toenail, with crumbling and irregular borders. The surface of the nails looks rough and uneven, and there is subungual debris. The surrounding skin appears intact without visible erythema or scaling." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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