Instructions to use dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("peft-internal-testing/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/scheduler.pt from dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8/resolve/main/last-checkpoint/scheduler.pt
- Command line
-
hf download hf://dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8/last-checkpoint/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8/resolve/main/last-checkpoint/scheduler.pt
1.06 kB
- Xet hash:
- a512547782317918bcd404ba961f11b96cc6513cfc85fa208fc289d3e6f20c7a
- Size of remote file:
- 1.06 kB
- SHA256:
- 2def2cd24154d8cecbaa07c36ae27e5ebb9b7273a78abfea27aa67c480e4ae2b
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