Instructions to use dada22231/593ff86e-d5f0-40b5-96ea-1cbe764a6df4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/593ff86e-d5f0-40b5-96ea-1cbe764a6df4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-7B") model = PeftModel.from_pretrained(base_model, "dada22231/593ff86e-d5f0-40b5-96ea-1cbe764a6df4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c8dc5ec76022dbfdf66216caeccd613fe227986f75ed79aa6f0c4d50811a445
- Size of remote file:
- 6.84 kB
- SHA256:
- f34142c8dd23b0e1a1c688ad7c468160b62fca80d4849c2beda645f8828587fe
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