Instructions to use Playingyoyo/aLLoyM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- Unsloth Studio
How to use Playingyoyo/aLLoyM 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 Playingyoyo/aLLoyM 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 Playingyoyo/aLLoyM to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Playingyoyo/aLLoyM to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Playingyoyo/aLLoyM", max_seq_length=2048, )
- Xet hash:
- d1fabbf9f1da513e6795e5a24853c459d1a5336dcdb204e5dd3f184119901c20
- Size of remote file:
- 228 MB
- SHA256:
- 2d0cba4e693fabfb654f1639eb1fa43761254eac55e53672d663000f37832243
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.