Instructions to use rb3212/kgpt_llm31_ft_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rb3212/kgpt_llm31_ft_lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rb3212/kgpt_llm31_ft_lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use rb3212/kgpt_llm31_ft_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 rb3212/kgpt_llm31_ft_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 rb3212/kgpt_llm31_ft_lora to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for rb3212/kgpt_llm31_ft_lora to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="rb3212/kgpt_llm31_ft_lora", max_seq_length=2048, )
- Xet hash:
- 773f09ec1b9abce61e5db542df63458f399615c69d67008d275946aa3dc077c3
- Size of remote file:
- 168 MB
- SHA256:
- 1a1870c38e1d8aeda8c8a5b9380a70e90de09dd5aa4a050ee2c53ca1599a30ce
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