Instructions to use beast33/38d28935-f58b-4d42-9ecd-9aac981f2592 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/38d28935-f58b-4d42-9ecd-9aac981f2592 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-7b-it") model = PeftModel.from_pretrained(base_model, "beast33/38d28935-f58b-4d42-9ecd-9aac981f2592") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- afa4d70c3759cc3133eb7e644acdcbbb710d1585a2a34adf554692a9c6044c48
- Size of remote file:
- 100 MB
- SHA256:
- 25019683ebdb3078d43bf3008691c6c1d39bed93d1b74550a016f60911b1e82e
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