Instructions to use socius/Smoltaur-0.4B-LoRA-r64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use socius/Smoltaur-0.4B-LoRA-r64 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-360M") model = PeftModel.from_pretrained(base_model, "socius/Smoltaur-0.4B-LoRA-r64") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use socius/Smoltaur-0.4B-LoRA-r64 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 socius/Smoltaur-0.4B-LoRA-r64 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 socius/Smoltaur-0.4B-LoRA-r64 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for socius/Smoltaur-0.4B-LoRA-r64 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="socius/Smoltaur-0.4B-LoRA-r64", max_seq_length=2048, )
- Xet hash:
- 42433b6b9418163ce31615241ad103e930542bdb91273b454832e534b24868d3
- Size of remote file:
- 71.1 MB
- SHA256:
- b3e51d2cd0682741158da33bb26c761afc60027c38146a6cd88d0f8776f0fc12
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.