Instructions to use HikMiz/loan-default-explainer-1b-v2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- Unsloth Studio
How to use HikMiz/loan-default-explainer-1b-v2.0 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 HikMiz/loan-default-explainer-1b-v2.0 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 HikMiz/loan-default-explainer-1b-v2.0 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for HikMiz/loan-default-explainer-1b-v2.0 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="HikMiz/loan-default-explainer-1b-v2.0", max_seq_length=2048, )
loan-default-explainer-1b-v2.0
LoRA fine-tune of unsloth/Llama-3.2-1B-Instruct, trained to write structured markdown
loan assessment memos from SHAP-based credit risk model output.
- Format: fp16 merged safetensors (not quantized)
- Base model: unsloth/Llama-3.2-1B-Instruct
- Chat template: standard Llama-3.2 template (system/user/assistant), unmodified — including the default "Cutting Knowledge Date / Today Date" system-turn boilerplate, since training data was generated with it present. Serve with the same template; stripping it at inference time will not match training.
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Model tree for HikMiz/loan-default-explainer-1b-v2.0
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