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:
- 032e16931df217f0d70c532e4b6b2b0159f81c8c4aa50d467a3a99211cbe8365
- Size of remote file:
- 73.9 MB
- SHA256:
- 7722e03890a92dcf7ccd89f30c9064edc2b22647e1a86ec0742d3f0a2240a317
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