Instructions to use Omartificial-Intelligence-Space/Arabic-DeepSeek-R1-Distill-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Omartificial-Intelligence-Space/Arabic-DeepSeek-R1-Distill-8B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/DeepSeek-R1-Distill-Llama-8B-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "Omartificial-Intelligence-Space/Arabic-DeepSeek-R1-Distill-8B") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Omartificial-Intelligence-Space/Arabic-DeepSeek-R1-Distill-8B 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 Omartificial-Intelligence-Space/Arabic-DeepSeek-R1-Distill-8B 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 Omartificial-Intelligence-Space/Arabic-DeepSeek-R1-Distill-8B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Omartificial-Intelligence-Space/Arabic-DeepSeek-R1-Distill-8B to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Omartificial-Intelligence-Space/Arabic-DeepSeek-R1-Distill-8B", max_seq_length=2048, )
- Xet hash:
- 85ad5c8944ff5c073c022c58ae980d26c3527c588935c913dd82f733e95103c6
- Size of remote file:
- 17.2 MB
- SHA256:
- d91915040cfac999d8c55f4b5bc6e67367c065e3a7a4e4b9438ce1f256addd86
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