Instructions to use Shabdobhedi/Arabic-Law-Meta-Llama-3.2-1B-Instruct-bnb-4bit-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shabdobhedi/Arabic-Law-Meta-Llama-3.2-1B-Instruct-bnb-4bit-LoRA with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Shabdobhedi/Arabic-Law-Meta-Llama-3.2-1B-Instruct-bnb-4bit-LoRA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Shabdobhedi/Arabic-Law-Meta-Llama-3.2-1B-Instruct-bnb-4bit-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 Shabdobhedi/Arabic-Law-Meta-Llama-3.2-1B-Instruct-bnb-4bit-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 Shabdobhedi/Arabic-Law-Meta-Llama-3.2-1B-Instruct-bnb-4bit-LoRA to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Shabdobhedi/Arabic-Law-Meta-Llama-3.2-1B-Instruct-bnb-4bit-LoRA to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Shabdobhedi/Arabic-Law-Meta-Llama-3.2-1B-Instruct-bnb-4bit-LoRA", max_seq_length=2048, )
- Xet hash:
- f02b5d231aeb56eb4bf185db71ce9bb0bfe92f0c3c200913b83bcd61ce81561b
- Size of remote file:
- 45.1 MB
- SHA256:
- 79c4a853907ccbef71fa47f718e91ac6594038fe1b2655bf9e51a0a77f66c250
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.