Instructions to use dbaysal/code-unit-unlearning-qwen2_5_coder_3b-prod_kl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dbaysal/code-unit-unlearning-qwen2_5_coder_3b-prod_kl with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-3B") model = PeftModel.from_pretrained(base_model, "dbaysal/code-unit-unlearning-qwen2_5_coder_3b-prod_kl") - Notebooks
- Google Colab
- Kaggle
File size: 884 Bytes
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2026-07-06T14:41:22,custom_hf_code_unit_qwen2_5_coder_3b_prod_kl,57aef574-9dd6-4d30-8b63-8dc458bb262e,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,202.57924974896014,0.011952308597600561,5.90006558540032e-05,42.5,189.9816321594595,324.7722086906433,0.0023907724891517623,0.01171962659793735,0.018268889631281957,0.03237928871837107,United States,USA,virginia,,,Linux-6.8.0-1051-azure-x86_64-with-glibc2.39,3.11.15,2.8.4,96,AMD EPYC 7V13 64-Core Processor,1,1 x NVIDIA A100 80GB PCIe,-78.3877,36.6694,866.0592231750488,machine,N,1.0
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