Wolof LoRA Adapter

This repository contains a LoRA adapter fine-tuned for a classroom demo on Wolof instruction following in Senegalese/African contexts.

Base Model

  • Qwen/Qwen3-0.6B

Intended Use

This adapter is designed for teaching:

  • instruction fine-tuning,
  • LoRA deployment,
  • local inference,
  • basic evaluation with Exact Match, F1, BLEU, ROUGE-L, and perplexity.

It is not a production Wolof assistant.

Loading Example

from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer

base_model = "Qwen/Qwen3-0.6B"
adapter_id = "YOUR_USERNAME/YOUR_REPO"

tokenizer = AutoTokenizer.from_pretrained(adapter_id, trust_remote_code=True)
base = AutoModelForCausalLM.from_pretrained(base_model, trust_remote_code=True)
model = PeftModel.from_pretrained(base, adapter_id)

Training Setup

  • LoRA rank: 16
  • LoRA alpha: 32
  • Target modules: attention and MLP projection layers
  • Dataset schema: instruction, input, output
  • Chat template rendered without hidden thinking traces when supported.

Limitations

The dataset is small and classroom-oriented. The model may repeat short Wolof phrases or fail outside the covered categories. Evaluate before reuse.

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