Instructions to use OliverSlivka/qwen2.5-7b-itemset-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use OliverSlivka/qwen2.5-7b-itemset-extractor with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-7B-Instruct") model = PeftModel.from_pretrained(base_model, "OliverSlivka/qwen2.5-7b-itemset-extractor") - Notebooks
- Google Colab
- Kaggle
Qwen2.5-7B SFT Frequent Itemset Extractor
This repository stores the exact PEFT LoRA SFT adapter used for the thesis
evaluation. It is intended to be loaded on top of Qwen/Qwen2.5-7B-Instruct with PEFT.
- Adapter checkpoint SHA-256:
f1dfb89164225c3f1f107a486271acab6c2d076e791241360bdc0d6466e416e2 - Expected loader:
Qwen2ForCausalLM.from_pretrained('Qwen/Qwen2.5-7B-Instruct', quantization_config=NF4, attn_implementation="sdpa")plusPeftModel.from_pretrained(...) - Expected eval profile:
primary_v3two-phase decoding
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