wanglab/Qwen3-1.7B-go-with-protein

Qwen3-1.7B-GO

Qwen3 1.7B model enhanced with pre-trained Gene Ontology (GO) term embeddings.

Model Description

This model is based on Qwen3 1.7B and includes:

• Pre-trained embeddings for GO terms
• Special tokens for protein sequence handling
• Fine-tuned on GO term descriptions and relationships

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("wanglab/Qwen3-1.7B-go")
tokenizer = AutoTokenizer.from_pretrained("wanglab/Qwen3-1.7B-go")

# Example with GO terms
text = "What is the function of GO:0008150?"
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

GO Terms

The model includes embeddings for Gene Ontology terms, allowing it to understand and reason about:

• Biological processes (GO:0008150)
• Molecular functions (GO:0003674)
• Cellular components (GO:0005575)

Training

GO embeddings were pre-trained using QLora on GO term descriptions and relationships.