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 Studio
How to use cn0303/fitcheck-spec-parser 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 cn0303/fitcheck-spec-parser 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 cn0303/fitcheck-spec-parser to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for cn0303/fitcheck-spec-parser to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="cn0303/fitcheck-spec-parser", max_seq_length=2048, )
- Xet hash:
- d0232be04119391e84a5d331c1e83b97e18dd2f9d38a5bab644133da9913f0e1
- Size of remote file:
- 69.8 MB
- SHA256:
- 7da9d72df630128f602da0724e78f33b98406752ba821b998ea2be521f90e6f4
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