Instructions to use Phuree/pluto_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Phuree/pluto_lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Phuree/pluto_lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Phuree/pluto_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 Phuree/pluto_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 Phuree/pluto_lora to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Phuree/pluto_lora to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Phuree/pluto_lora", max_seq_length=2048, )
- Xet hash:
- d0c9769de7c0bd9aa02da2831e6415ddd911e968fa23cdd9fcb3422a20aa0ef6
- Size of remote file:
- 257 MB
- SHA256:
- 016aaca34ff94e95f40504151c39da0fa2bf513add2a805fa1795c68d956b17e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.