Instructions to use LightFury9/3B-countdown-250 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LightFury9/3B-countdown-250 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("LightFury9/3B-countdown-250", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use LightFury9/3B-countdown-250 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 LightFury9/3B-countdown-250 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 LightFury9/3B-countdown-250 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for LightFury9/3B-countdown-250 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="LightFury9/3B-countdown-250", max_seq_length=2048, )
- Xet hash:
- 1d49a119f61e3a1f956905dd8d7fba46a85ed1e753834c441e447f44d6fc9c55
- Size of remote file:
- 5.82 kB
- SHA256:
- 8ca6359153a01eba37d9ee1a25d565305bc45d40088140ea2f24baf3975ae2bc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.