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:
- b3b7d94b881d95acfab3acb18417fc2cd5c59c5303e33b41b5b44f7340d42aa8
- Size of remote file:
- 16.4 kB
- SHA256:
- d2dccc5dfee633f35423899ea5dc708ad53b1ab99ecd48622cfc91d18fc50497
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