Instructions to use Aivesa/751f1e72-59b6-456b-ab88-b74d3a309aa7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Aivesa/751f1e72-59b6-456b-ab88-b74d3a309aa7 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, "Aivesa/751f1e72-59b6-456b-ab88-b74d3a309aa7") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6fefe9d2f720df2c0af561735a3d448bf920922a6ac68ac242b36315f935b3d
- Size of remote file:
- 83.9 MB
- SHA256:
- 5d31b183c0237d799be486e8a0c79845de8a7754c8e62dad0895e9635b0fbd5f
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