Instructions to use BUAIR/tiny-aya-earth-uganda-agri-v1-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use BUAIR/tiny-aya-earth-uganda-agri-v1-final with PEFT:
Base model is not found.
- Notebooks
- Google Colab
- Kaggle
Configuration Parsing Warning:In adapter_config.json: "peft.base_model_name_or_path" must be a string
Tiny Aya Earth Uganda Agri v1 Final (BUAIR/tiny-aya-earth-uganda-agri-v1-final)
PEFT/LoRA adapter for Uganda agricultural question answering, maintained by BUAIIR — Busitema University AI & Innovation Research Lab.
This is the BUAIR org release. Source copy:
Bateesa/tiny-aya-earth-uganda-agri-v1-final.
Load
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = "CohereForAI/aya-expanse-8b" # or the base used during training
tokenizer = AutoTokenizer.from_pretrained("BUAIR/tiny-aya-earth-uganda-agri-v1-final")
model = AutoModelForCausalLM.from_pretrained(base)
model = PeftModel.from_pretrained(model, "BUAIR/tiny-aya-earth-uganda-agri-v1-final")
Updated: 2026-08-13
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