Instructions to use prxy5605/972a7773-df3e-41a6-ae33-0a2e4cb288cd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use prxy5605/972a7773-df3e-41a6-ae33-0a2e4cb288cd with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B") model = PeftModel.from_pretrained(base_model, "prxy5605/972a7773-df3e-41a6-ae33-0a2e4cb288cd") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d455cb2d2097d81450993498eaa7a46d6064db468b2e0aeabf100a7c67c0a814
- Size of remote file:
- 141 MB
- SHA256:
- 11b6432a580f6f75640e2b65bf1ae7cef708a6e0ea09521c78212a7e3e3c8049
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