metadata
license: apache-2.0
base_model: google/txgemma-9b-predict
tags:
- gemma
- txgemma
- ec-number
- biochemical-reactions
- lora
- gemma4ec
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