sentence-transformers How to use Jbbok/my-embeddinggemma-2-sec with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("Jbbok/my-embeddinggemma-2-sec")
sentences = [
"What was Honeywell International's other (income) expense in 2025?",
"company: HONEYWELL INTERNATIONAL INC | ticker: HON | type: 10-K | report_date: 2025-12-31\n**Other (Income) Expense**\n\n### Other (income) expense\n\n- 2025: $(1,247)\n- 2024: $(843)\n- 2023: $(830)",
"company: HONEYWELL INTERNATIONAL INC | ticker: HON | type: 10-K | report_date: 2025-12-31\n**INCOME BEFORE TAXES**\n\n### U.S.\n(us-gaap:IncomeLossFromContinuingOperationsBeforeIncomeTaxesDomestic)\n\n- 2025: $373 million [=373,000,000 USD]\n- 2024: $1,442 million [=1,442,000,000 USD]\n- 2023: $1,652 million [=1,652,000,000 USD]\n\n### Non-U.S.\n(us-gaap:IncomeLossFromContinuingOperationsBeforeIncomeTaxesForeign)\n\n- 2025: 5,103 million [=5,103,000,000 USD]\n- 2024: 4,802 million [=4,802,000,000 USD]\n- 2023: 4,539 million [=4,539,000,000 USD]\n\n### Total Income before taxes\n(us-gaap:IncomeLossFromContinuingOperationsBeforeIncomeTaxesExtraordinaryItemsNoncontrollingInterest)\n\n- 2025: $5,476 million [=5,476,000,000 USD]\n- 2024: $6,244 million [=6,244,000,000 USD]\n- 2023: $6,191 million [=6,191,000,000 USD]",
"company: Mastercard Inc | ticker: MA | type: 10-K | report_date: 2025-12-31\nThe table below shows a summary of the cash flows from operating, investing and financing activities:\n\n*(unit: (in millions))*\n\n### Net cash provided by operating activities (For the Years Ended December 31,)\n\n- 2025: $17,648\n- 2024: $14,780\n- 2023: $11,980\n\n### Net cash used in investing activities (For the Years Ended December 31,)\n\n- 2025: (1,362)\n- 2024: (3,402)\n- 2023: (1,351)\n\n### Net cash used in financing activities (For the Years Ended December 31,)\n\n- 2025: (14,179)\n- 2024: (10,836)\n- 2023: (9,488)"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
