Instructions to use apriasmoro/9b7b5cec-4412-4dd7-9b96-aec92982f6c3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use apriasmoro/9b7b5cec-4412-4dd7-9b96-aec92982f6c3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama-chat") model = PeftModel.from_pretrained(base_model, "apriasmoro/9b7b5cec-4412-4dd7-9b96-aec92982f6c3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 186bab636b453245f2cdbf8c67e8f4ccde04bec0a04df7eeb0f8fee8d823394f
- Size of remote file:
- 6.78 kB
- SHA256:
- 83b28ba5050814e3cd06c2534739e17467daf40046f1e539c07d98723ca33e92
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