Instructions to use dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("dunzhang/stella_en_1.5B_v5") model = PeftModel.from_pretrained(base_model, "dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dimasik2987/c4fd30f8-9bed-4199-bfca-cc8c495b627b/resolve/main/last-checkpoint/training_args.bin
6.84 kB
- Xet hash:
- 6a959d755086027a7002023528747a065a071693ce8a02820f12afd100419692
- Size of remote file:
- 6.84 kB
- SHA256:
- fe585d38c0f55dd136852a33fb6d7b28d60b9eb8a75d9f4cd7d4ef61cd35b455
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