The adapter is intended for research on temporal reasoning and African economic, social and development data. It should be evaluated carefully before use in consequential decision-making.

Loading

python

import torch
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer

base_model_id = "google/gemma-4-E4B-it"
adapter_id = "YOUR_HF_USERNAME/gemma-4-e4b-afritemp"

tokenizer = AutoTokenizer.from_pretrained(adapter_id)
base_model = AutoModelForCausalLM.from_pretrained(
    base_model_id,
    dtype=torch.bfloat16,
    device_map="auto",
)
model = PeftModel.from_pretrained(base_model, adapter_id)

Framework versions

PEFT 0.19.1

africatic/atic

Gemma 4 E4B — AfriTemp LoRA

Training setup

Intended use

Loading

Framework versions

africatic/
atic