Instructions to use eeeebbb2/9b7fb9cc-43da-4e59-b670-c828b1605eb3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/9b7fb9cc-43da-4e59-b670-c828b1605eb3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/codegemma-7b") model = PeftModel.from_pretrained(base_model, "eeeebbb2/9b7fb9cc-43da-4e59-b670-c828b1605eb3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f753cab4e7a1ba7dc9d7c049587898dd3406bcf5813ab292cb1e45bd4733396c
- Size of remote file:
- 400 MB
- SHA256:
- 4e223615942ad42399e37786e644d9b87964fc13a56d8e0aa10263166d9191d5
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