Instructions to use dimasik87/7e2b7022-0bfa-480d-b146-b5e0c308b56e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/7e2b7022-0bfa-480d-b146-b5e0c308b56e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Math-1.5B") model = PeftModel.from_pretrained(base_model, "dimasik87/7e2b7022-0bfa-480d-b146-b5e0c308b56e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca3f2f40018df7ba9d950e9fbe7d8305f36fd07c3482eaa45e668d476a4b0c0d
- Size of remote file:
- 74 MB
- SHA256:
- ee0af7c90262982375ee186290ebaa1bafa3c3b921f3c41655e785f5e23e5a0c
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