sentence-transformers How to use Farrukhceo/litfx-nomic-embed with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("Farrukhceo/litfx-nomic-embed", trust_remote_code=True)
sentences = [
"search_query: wat is a slash command?",
"search_document: Community moderation features: Google Cloud Vision SafeSearch auto-rejects adult, violent, or racy uploaded images. Messages with 3 or more reports are auto-hidden pending review. Community bot with engagement scheduler, filters, and slash commands. Admin audit trails for all moderation actions. User presence shows online, idle, and DND states. Community profiles display role (CEO, admin, moderator, student), subscription tier, TQS score, and badges.",
"search_document: Community has 9 or more channels organized by topic. Trading channels: entries, analysis, front-testing, crypto, stock, questions, stop-losses, fundamental-analysis, trade-ideas. General channels: announcement, general-chat, homework. Results channel and sunday-talk (weekly mindset). Premium-gated channels: homework, front-testing, entries, stop-losses, questions. Features include text plus multiple images, trade result cards, emoji reactions, reply threads, pinned messages, message editing, and admin moderation tools. Exclusive premium community channels are English-language.",
"search_document: General sizing formula: position size equals account risk amount divided by stop distance value. This keeps risk constant across different instruments and setup sizes instead of using arbitrary lot size choices."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
