Instructions to use 0x1202/e41c2262-6ee1-457b-a517-b45596d9afaf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 0x1202/e41c2262-6ee1-457b-a517-b45596d9afaf with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-135M-Instruct") model = PeftModel.from_pretrained(base_model, "0x1202/e41c2262-6ee1-457b-a517-b45596d9afaf") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from 0x1202/e41c2262-6ee1-457b-a517-b45596d9afaf: direct link, hf CLI and curl.
- Browser
- Download file 40.2 MB
-
https://huggingface.co/0x1202/e41c2262-6ee1-457b-a517-b45596d9afaf/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://0x1202/e41c2262-6ee1-457b-a517-b45596d9afaf/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/0x1202/e41c2262-6ee1-457b-a517-b45596d9afaf/resolve/main/last-checkpoint/optimizer.pt
40.2 MB
- Xet hash:
- 5b5665a573c19af4050bd6133b35e5fece0cef60dd2a77e0d16942344b3d882f
- Size of remote file:
- 40.2 MB
- SHA256:
- 12519ddd34e29ebeaec3ce08d34a7527c7208b902ae9bae76592b9297767081b
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