Instructions to use hnuka/v3_lora_adapter_base-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hnuka/v3_lora_adapter_base-sft with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hnuka/v3_lora_adapter_base-sft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use hnuka/v3_lora_adapter_base-sft 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 hnuka/v3_lora_adapter_base-sft 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 hnuka/v3_lora_adapter_base-sft to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for hnuka/v3_lora_adapter_base-sft to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="hnuka/v3_lora_adapter_base-sft", max_seq_length=2048, )
- Xet hash:
- 4658c038beadf3a8e4f18a8a6e9e305c09f7c97e3a0a5f65c9a439a4efa7fc97
- Size of remote file:
- 17.1 MB
- SHA256:
- 973fd736217a055c6cd01c85c4897f54d4b5f46ef1d9c27b75467d7ff301ff0f
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