Instructions to use nhungphammmmm/c72cb38a-0b3c-4545-8a39-ca8192123f62 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhungphammmmm/c72cb38a-0b3c-4545-8a39-ca8192123f62 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-beta") model = PeftModel.from_pretrained(base_model, "nhungphammmmm/c72cb38a-0b3c-4545-8a39-ca8192123f62") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 230af60857d7f1eab950d9558546b6840d5e715eac2c415fc630993db7cc4505
- Size of remote file:
- 84 MB
- SHA256:
- 748382f687f4fa2f742652a3395ad1dce6e1fba64e2deb7fa96e6be93e8a1f32
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