Instructions to use KhetLink/Fasal-1B-LoRA-Heavy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KhetLink/Fasal-1B-LoRA-Heavy with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("KhetLink/Fasal-1B-LoRA-Heavy", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use KhetLink/Fasal-1B-LoRA-Heavy 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 KhetLink/Fasal-1B-LoRA-Heavy 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 KhetLink/Fasal-1B-LoRA-Heavy to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for KhetLink/Fasal-1B-LoRA-Heavy to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="KhetLink/Fasal-1B-LoRA-Heavy", max_seq_length=2048, )
- Xet hash:
- ead71b9648076c346f05546e3d5aba2546d742e3ba2a82edf18d18f8de472c06
- Size of remote file:
- 295 MB
- SHA256:
- 7298ad96fabc5f4670aaee72409e1dbab6420ae47bc91629dca3edebbc8ee0d3
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