npc0/Qwen3-Embedding-0.6B-OED

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