Instructions to use MariChatmen/qwen-andaluh-0.8b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MariChatmen/qwen-andaluh-0.8b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-0.8B") model = PeftModel.from_pretrained(base_model, "MariChatmen/qwen-andaluh-0.8b-lora") - Notebooks
- Google Colab
- Kaggle
Qwen-Andaluh 0.8B LoRA
LoRA adapter for Qwen/Qwen3.5-0.8B trained as the non-persona
Qwen-Andaluh checkpoint.
The intended behaviour is simple:
System prompt: Eres un asistente
Input: Spanish or Andal没h
Output: Andal没h EPA
This is an adapter release, not a merged model.
Training Stages
- Andal没h continued pretraining / CPT.
- Accent SFT.
- Accent ORPO preference tuning.
The source data was generated from Spanish instruction rows by filtering licence-compatible Spanish examples, protecting fragile spans, converting assistant messages to Andal没h EPA, converting a controlled share of user messages to Andal没h EPA, and restoring URLs, paths, code, package names and model IDs unchanged.
Adapter Details
- Base model:
Qwen/Qwen3.5-0.8B - Adapter type: LoRA / QLoRA
- Rank: 16
- Alpha: 32
- Dropout: 0.05
- Target modules:
q_proj,k_proj,v_proj,o_proj,gate_proj,up_proj,down_proj
Use
from peft import AutoPeftModelForCausalLM
from transformers import AutoTokenizer
model_id = "MariChatmen/qwen-andaluh-0.8b-lora"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoPeftModelForCausalLM.from_pretrained(model_id, device_map="auto")
Limitations
- Experimental research adapter.
- May leak standard Spanish.
- May produce imperfect Andal没h EPA.
- Not an official linguistic standard.
Related
- Persona dataset: https://huggingface.co/datasets/MariChatmen/MariChatmen-Persona
- AndaluGeeks EPA: https://andaluh.es/epa-2/
andaluh-py: https://github.com/andalugeeks/andaluh-py
- Downloads last month
- 4