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:
- 179a015e3c3897b5ff65bc6bf9b6301fd3ede2b1ddcaba4161fc55615729f59e
- Size of remote file:
- 5.71 kB
- SHA256:
- 8f8e98a677c85e582b638e8146ba71c0c63999a099ef89ce89c773a388fe15a6
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