Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
dense
Generated from Trainer
dataset_size:369891
loss:TripletLoss
Instructions to use Mercity/memory-retrieval-jina-v3-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Mercity/memory-retrieval-jina-v3-lora with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Mercity/memory-retrieval-jina-v3-lora") sentences = [ "Echoes in the Alley is evolving into this brooding masterpiece, and heightening Jax's voice has me buzzing—let's iterate on a sample monologue to make it sing with poetic rhythm!", "Sam, the lead researcher, strongly advocated in the last team meeting for temporarily excluding the Hawaii lab's pH data from the primary analysis until the September 15th deadline.", "Maria has a strong, established working relationship with the in-house data science team, who recently developed a proprietary lookalike modeling tool that integrates directly with the existing ad platform.", "In a previous collaboration, Taylor's roommate, cast as Jax, delivered a standout improvised monologue during a poetry reading event that captured the character's vulnerability without any scripted props, earning praise from peers for its raw authenticity." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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