Instructions to use 0x1202/8318414d-3946-4a84-a833-c3431b05498b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 0x1202/8318414d-3946-4a84-a833-c3431b05498b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-random-GemmaForCausalLM") model = PeftModel.from_pretrained(base_model, "0x1202/8318414d-3946-4a84-a833-c3431b05498b") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from 0x1202/8318414d-3946-4a84-a833-c3431b05498b: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/0x1202/8318414d-3946-4a84-a833-c3431b05498b/resolve/main/training_args.bin
- Command line
-
hf download hf://0x1202/8318414d-3946-4a84-a833-c3431b05498b/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/0x1202/8318414d-3946-4a84-a833-c3431b05498b/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- fe8e8e72712f210770e6ad9c0b3bc8dd301afdf7f1f7d2c02fa6a7438745257f
- Size of remote file:
- 6.84 kB
- SHA256:
- f6b1a54ff8db39f84608c67eb50bdd3beb6f8fa3440dbdca750987d8ceece02b
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