How to use yasserrmd/oncology-gemma-300m-emb with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yasserrmd/oncology-gemma-300m-emb") sentences = [ "What are the criteria for evaluating the therapeutic efficacy of tumor treatment?\n", "Detecting the sentinel node in gastric cancer is challenging due to the complex lymphatic drainage of the stomach. The lymphatic network in the stomach is considerably more complex than that of ectodermal organs like breast and skin, making it difficult to identify the sentinel node accurately. This complexity is attributed to the complex embryological development of the stomach.", "The criteria for evaluating the therapeutic efficacy of tumor treatment include measuring and calculating the sum of the longest diameter of all target lesions and comparing it with the baseline sum of longest diameters. The objective tumor evaluation criteria include complete remission, partial remission, progressive disease, and stable disease.", "Low levels of GAS7C mRNA expression have been frequently detected in lung cancer samples, particularly in stage IV and metastatic patients. This suggests an association between low GAS7C expression and cancer progression. Additionally, low GAS7C expression has been correlated with poorer survival in late-stage lung cancer patients from Asian and Caucasian populations. These findings indicate that GAS7C may serve as a prognostic biomarker in lung cancer patients with metastasis. Furthermore, it is possible that GAS7C may act as a metastasis suppressor in other types of cancer." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
