Instructions to use alchemist69/c40cb2d8-d318-48b7-bf71-35be915e0637 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use alchemist69/c40cb2d8-d318-48b7-bf71-35be915e0637 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "alchemist69/c40cb2d8-d318-48b7-bf71-35be915e0637") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from alchemist69/c40cb2d8-d318-48b7-bf71-35be915e0637: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/alchemist69/c40cb2d8-d318-48b7-bf71-35be915e0637/resolve/main/training_args.bin
- Command line
-
hf download hf://alchemist69/c40cb2d8-d318-48b7-bf71-35be915e0637/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/alchemist69/c40cb2d8-d318-48b7-bf71-35be915e0637/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 0d828b55a00528381ae5af27e3f8ef8df64d4dbe283128f8ad53d1c74efe0aee
- Size of remote file:
- 6.84 kB
- SHA256:
- 016d22d24a50a039625248ae01a568327b963bd5fa435250e13865a352826d10
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