Model Card for Model ID
Based on Qwen3 Embedding 0.6 finetuned on Oxford English Dictionary for word and sentence relationship association.
Experimental model not for production use.
Model Details
Model Description
- Developed by: [More Information Needed]
- Language(s) (NLP): English
- License: Apache 2.0
- Finetuned from model: Qwen/Qwen3-Embedding-0.6B
Uses
Model is intented to be used in embedding and searching for words and short phrases
Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("npc0/Qwen3-Embedding-0.6B-OED")
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]
Training Details
Training Data
[More Information Needed]
Training Procedure
Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type: NVIDIA T4 * 2
- Hours used: 6.5 hours
- Cloud Provider: Google
- Carbon Emitted: 0.01 kg CO_2
Framework versions
- PEFT 0.17.1