Instructions to use dzanbek/df0fa936-3f41-4d65-8622-edc329a19b97 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/df0fa936-3f41-4d65-8622-edc329a19b97 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("scb10x/llama-3-typhoon-v1.5-8b-instruct") model = PeftModel.from_pretrained(base_model, "dzanbek/df0fa936-3f41-4d65-8622-edc329a19b97") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b222a776af29ce62a7d056ebe83f9730a54cab53aca6f6aee0d18d37491e561b
- Size of remote file:
- 168 MB
- SHA256:
- c7926a0891f305c419f0d63a044122a3b5e13090f036e8a930120d880042c384
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