Instructions to use lvogel123/Llama-3.2-3B-poem-god-lora-F32-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lvogel123/Llama-3.2-3B-poem-god-lora-F32-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lvogel123/Llama-3.2-3B-poem-god-lora-F32-GGUF", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use lvogel123/Llama-3.2-3B-poem-god-lora-F32-GGUF 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 lvogel123/Llama-3.2-3B-poem-god-lora-F32-GGUF 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 lvogel123/Llama-3.2-3B-poem-god-lora-F32-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for lvogel123/Llama-3.2-3B-poem-god-lora-F32-GGUF to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="lvogel123/Llama-3.2-3B-poem-god-lora-F32-GGUF", max_seq_length=2048, )
- Xet hash:
- 3d8eea19ac68edd34093f0abfe7f2faf921dc3b2d344f818ac102c03669340da
- Size of remote file:
- 97.3 MB
- SHA256:
- 835ebcb4380355e8621bcaa5a3ca0c1816a963afd8978dfbc2c46540d22e33a3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.