Instructions to use 0x1202/c593a074-ad0a-4259-bc18-4ac31e2ac0aa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 0x1202/c593a074-ad0a-4259-bc18-4ac31e2ac0aa with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-128k-instruct") model = PeftModel.from_pretrained(base_model, "0x1202/c593a074-ad0a-4259-bc18-4ac31e2ac0aa") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from 0x1202/c593a074-ad0a-4259-bc18-4ac31e2ac0aa: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/0x1202/c593a074-ad0a-4259-bc18-4ac31e2ac0aa/resolve/main/training_args.bin
- Command line
-
hf download hf://0x1202/c593a074-ad0a-4259-bc18-4ac31e2ac0aa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/0x1202/c593a074-ad0a-4259-bc18-4ac31e2ac0aa/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 48259d8431de200cf3729560a8cb8ec10d2ee1568b00477b8193336d4e74a5e7
- Size of remote file:
- 6.84 kB
- SHA256:
- 2876561339e697318a8ea559e4b496ccb80a517e8ae87f7923f313f8890f0c9e
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