Instructions to use Louug/Qwen-4B-Darija-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Louug/Qwen-4B-Darija-LoRA with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Louug/Qwen-4B-Darija-LoRA", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Louug/Qwen-4B-Darija-LoRA with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Louug/Qwen-4B-Darija-LoRA to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Louug/Qwen-4B-Darija-LoRA to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Louug/Qwen-4B-Darija-LoRA to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Louug/Qwen-4B-Darija-LoRA", max_seq_length=2048, )
Uploaded model
- Developed by: Louug
- License: apache-2.0
- Finetuned from model : Qwen/Qwen3.5-4B
This qwen3_5 model was trained 2x faster with Unsloth
10% of the MBZUAI-Paris/Darija-SFT-Mixture was used to fine-tune the model, converged very poorly .. Wich gives room to upgrading :D
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