Instructions to use dipikakhullar/olmo-code-python3-text-only with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dipikakhullar/olmo-code-python3-text-only 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-python3-text-only") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dipikakhullar/olmo-code-python3-text-only: direct link, hf CLI and curl.
- Browser
- Download file 5.71 kB
-
https://huggingface.co/dipikakhullar/olmo-code-python3-text-only/resolve/main/training_args.bin
- Command line
-
hf download hf://dipikakhullar/olmo-code-python3-text-only/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dipikakhullar/olmo-code-python3-text-only/resolve/main/training_args.bin
5.71 kB
- Xet hash:
- 3a23ad4e5f870fc83f3be5d8e858ec7e454aedf7171b70805f66dde24ae4d533
- Size of remote file:
- 5.71 kB
- SHA256:
- 19c20e1c890c1e816d490803c0d52203174fd680a82d7137f53c061dbb8ac86f
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