Instructions to use FirstPotatoCoder/Ayaka-1332 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use FirstPotatoCoder/Ayaka-1332 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/csm-1b") model = PeftModel.from_pretrained(base_model, "FirstPotatoCoder/Ayaka-1332") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from FirstPotatoCoder/Ayaka-1332: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/FirstPotatoCoder/Ayaka-1332/resolve/main/training_args.bin
- Command line
-
hf download hf://FirstPotatoCoder/Ayaka-1332/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/FirstPotatoCoder/Ayaka-1332/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 553bb02658f89d8ef8cf6b59bf1e827f3e8618e541a51c928b620d91fa3ec6ab
- Size of remote file:
- 5.24 kB
- SHA256:
- 3db12e78a7b0f3c6b3cb7b57ff5c08c99fb3224a8b31f2613a553bc17b7d276b
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