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
Delete training_args.bin with huggingface_hub
Browse files- training_args.bin +0 -3
training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:032270e6368227ad368917b2e6058d48d8cef1178f67731a191dc123328ba3f8
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size 5240
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