Instructions to use nhung02/9f910db6-66d8-449f-9562-c7dc40048ccb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung02/9f910db6-66d8-449f-9562-c7dc40048ccb 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, "nhung02/9f910db6-66d8-449f-9562-c7dc40048ccb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69deda217f92dca885f6416f63d3b38bac501f02f86a7c5af423d533b2db12c0
- Size of remote file:
- 83.9 MB
- SHA256:
- f9cbe1480a53832a25959d2ebe370f78859bc75135de9c86117f0bd287be7870
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