Instructions to use dada22231/d9b72381-1ad7-4fa7-9d6b-670f1c0cfa90 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/d9b72381-1ad7-4fa7-9d6b-670f1c0cfa90 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, "dada22231/d9b72381-1ad7-4fa7-9d6b-670f1c0cfa90") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98e4f6a215e3a2da5d7dea6080d1c5967f1c882a71796252740f00d4e840263d
- Size of remote file:
- 296 MB
- SHA256:
- 36e32de99fb88b2c63974e56f572312f78c61cb10e5b8c1aefd1932f2f850e36
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