Instructions to use dipikakhullar/olmo-code-python2-3-tagged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dipikakhullar/olmo-code-python2-3-tagged with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("allenai/OLMo-1B-hf") model = PeftModel.from_pretrained(base_model, "dipikakhullar/olmo-code-python2-3-tagged") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b43f65a8bad20cb40764a9ecb82b226b36e8340468c0c7f251b18b68f06eac8f
- Size of remote file:
- 16.4 kB
- SHA256:
- 1d3182ca5defe0a923e8098840a716023fb7e01c6c9c148cce40cd1b43dae769
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