Instructions to use dzanbek/12cec7cb-7cc2-4e1b-a0c3-2944779bd461 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/12cec7cb-7cc2-4e1b-a0c3-2944779bd461 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-1.7B") model = PeftModel.from_pretrained(base_model, "dzanbek/12cec7cb-7cc2-4e1b-a0c3-2944779bd461") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f109b52ab75813be0fc635aede9e0cd79c5abc659106ef5507014cc3c8394fca
- Size of remote file:
- 145 MB
- SHA256:
- 1145d99fe7f6d5e3f2a71269768ce2fbdb4aee31226b754f936f2b30e1e39fc1
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