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BSVGK
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Model Details
Model Provider
BSVGK
Model Tree
google/gemma-1.1-2b-it
Input Modalities
Output Modalities
Supported Functionality
This is the full merged model of Gemma 1.1 2B IT fine-tuned with LoRA to generate fluent, hallucination-free natural language drug descriptions from pharmaceutical RDF knowledge graph triples sourced from DrugBank. It was developed as part of a UEL–Depixen industrial placement research project focused on building trustworthy, domain-specific SLMs.
This is the recommended model for inference — no additional adapter loading required.
For the LoRA adapter only, use: 👉 BSVGK/gemma-1.1-2b-it-drugbank-kg2text-lora-v2
| Metric | Score |
|---|---|
| BLEU Score | 0.9737 |
| BERTScore F1 | 0.9896 |
| Fact F1 | 0.9966 |
| Hallucination Rate | 0.54% |
| Test Samples | 254 unseen DrugBank entries |
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained( "BSVGK/gemma-1.1-2b-it-drugbank-kg2text-merged-v2" ) model = AutoModelForCausalLM.from_pretrained( "BSVGK/gemma-1.1-2b-it-drugbank-kg2text-merged-v2" )
prompt = """Generate a natural language description from the following RDF triples:
Triples:
Description:"""
inputs = tokenizer(prompt, return_tensors="pt") outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0], skip_special_tokens=True))
| Merged Model v2 | LoRA Adapter v2 | |
|---|---|---|
| Inference | ✅ Direct — no base model needed | ❌ Requires base model + PEFT |
| Storage | Larger (full model) | Smaller (adapter only) |
| Speed | Faster to load | Slower to load |
| Recommended for | Production inference | Research & experimentation |
This model is intended for research purposes only. It should not be used for clinical decision-making or medical advice. Always consult a qualified healthcare professional.
@misc{bubathula2026drugbank_merged, author = {Sai Venkata Gopala Krishna Bubathula}, title = {Gemma 1.1 2B IT Merged Model v2: KG-to-Text Generation for DrugBank Pharmaceutical Data}, year = {2026}, publisher = {HuggingFace}, url = {https://huggingface.co/BSVGK/gemma-1.1-2b-it-drugbank-kg2text-merged-v2}, institution = {University of East London & Depixen} }
Sai Venkata Gopala Krishna Bubathula