Instructions to use Liquid1/Liquid1MAKB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Liquid1/Liquid1MAKB with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Liquid1/Liquid1MAKB", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Liquid1/Liquid1MAKB 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 Liquid1/Liquid1MAKB 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 Liquid1/Liquid1MAKB to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Liquid1/Liquid1MAKB to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Liquid1/Liquid1MAKB", max_seq_length=2048, )
- Xet hash:
- db3cbab07b594c59578d83b5cd2bf870250e34247c626162cd99cdf591c866dd
- Size of remote file:
- 122 MB
- SHA256:
- 6daad33f29c4fc6b872357155e90a7acf774fdb312cd4d4bf7f5333e55b1ee21
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