Instructions to use beast33/aec93490-b5fc-4a7d-9037-a5813cf76ddd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/aec93490-b5fc-4a7d-9037-a5813cf76ddd with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/codegemma-2b") model = PeftModel.from_pretrained(base_model, "beast33/aec93490-b5fc-4a7d-9037-a5813cf76ddd") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59efb5c3252b6291feef9b3a38ea4855332ef43de07aebc5b1513a5e3b6a3ba5
- Size of remote file:
- 6.78 kB
- SHA256:
- 9d329f93e185f612c4efce9828b6076938a704f16658a49da4aa35caaaf9a399
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