Text Generation
PEFT
Safetensors
lora
sft
structured-extraction
hardware-specs
qwen3
unsloth
conversational
Instructions to use cn0303/fitcheck-spec-parser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cn0303/fitcheck-spec-parser with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen3-1.7B") model = PeftModel.from_pretrained(base_model, "cn0303/fitcheck-spec-parser") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Commit History
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Card: add honest builder-blind sealed-test result (88.0% acc / 17.7% invented; fails the <5% gate; dev 1.2% was optimistic)
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Card: correct training-data sourcing (mixed vendor + community spec tables), dev-vs-sealed honesty
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Spec-parser LoRA r5: 91.6% field accuracy, 1.2% invented-field rate (dev set)
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initial commit
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