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Gemma4EC-9B-Predict

This repository contains the LoRA adapter for Gemma4EC, a model fine-tuned to predict Enzyme Commission (EC) numbers from biochemical reaction SMILES.

Base model

google/txgemma-9b-predict

Task

Input: biochemical reaction SMILES
Output: EC number (up to sub-subclass level)

Training

Parameter-efficient fine-tuning using LoRA
Few-shot prompt format

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_model = "google/txgemma-9b-predict"
adapter_repo = "PlanesLab/Gemma4EC-9B-Predict"

tokenizer = AutoTokenizer.from_pretrained(base_model)
model = AutoModelForCausalLM.from_pretrained(
    base_model,
    torch_dtype="auto",
    device_map="auto"
)

model = PeftModel.from_pretrained(model, adapter_repo)
model.eval()

Code

Full source code including training, inference and benchmarking scripts are available on:

https://github.com/PlanesLab/Gemma4EC

Citation

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