Sentence Similarity
sentence-transformers
Safetensors
multilingual
qwen2
reasoning-embedding
fine-tuned
embeddings
custom_code
text-embeddings-inference
Instructions to use lucaswychan/Qwen-2.5-1.5B-SimpleRL-Zoo-Reasoning-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lucaswychan/Qwen-2.5-1.5B-SimpleRL-Zoo-Reasoning-Embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lucaswychan/Qwen-2.5-1.5B-SimpleRL-Zoo-Reasoning-Embedding", trust_remote_code=True) sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
metadata
library_name: transformers
pipeline_tag: sentence-similarity
base_model: hkust-nlp/Qwen-2.5-1.5B-SimpleRL-Zoo
tags:
- reasoning-embedding
- transformers
- fine-tuned
- embeddings
license: apache-2.0
language:
- en
Qwen-2.5-1.5B-SimpleRL-Zoo-Reasoning-Embedding
This model is a fine-tuned version of hkust-nlp/Qwen-2.5-1.5B-SimpleRL-Zoo. It was fine-tuned for embedding analysis of reasoning models.