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 adapter_model.safetensors from dipikakhullar/olmo-code-python3-text-only: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/dipikakhullar/olmo-code-python3-text-only/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://dipikakhullar/olmo-code-python3-text-only/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/dipikakhullar/olmo-code-python3-text-only/resolve/main/adapter_model.safetensors
12.1 MB
- Xet hash:
- 574421a93da4cce4a4ac15a84ed7590c95372cae8e75b0b401caad4b2986e105
- Size of remote file:
- 12.1 MB
- SHA256:
- 5cf3dd66b5bb2fce32666cbeaa1a46b611ab925b60432203d28b4ba9fd5c7c0c
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