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:
- 56ef075a0369319b4c4f59c34a76248fc9ee7802a69bd543bebac9d393daff9f
- Size of remote file:
- 16.4 kB
- SHA256:
- 58322e7c33c8f14763aa2d5ea04e1f95bd6d3970507fdd77b436e51c893f45f3
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