Text Generation
PEFT
Safetensors
English
agriculture
uganda
qwen
lora
reasoning
buair
buaiir
conversational
Instructions to use BUAIR/Qwen3.3B-Agricultural-Reasoning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use BUAIR/Qwen3.3B-Agricultural-Reasoning 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
Qwen 3.3B Agricultural Reasoning (BUAIR/Qwen3.3B-Agricultural-Reasoning)
PEFT/LoRA adapter for agricultural reasoning and advisory, maintained by BUAIIR — Busitema University AI & Innovation Research Lab.
This is the BUAIR org release. Source copy:
Bateesa/Qwen3.3B-Agricultural-Reasoning.
Load
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = "Qwen/Qwen2.5-3B-Instruct" # confirm against adapter_config.json
tokenizer = AutoTokenizer.from_pretrained("BUAIR/Qwen3.3B-Agricultural-Reasoning")
model = AutoModelForCausalLM.from_pretrained(base)
model = PeftModel.from_pretrained(model, "BUAIR/Qwen3.3B-Agricultural-Reasoning")
Updated: 2026-08-13
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