Instructions to use adammandic87/7c12f244-4be8-4e78-94f8-ba87266f4032 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use adammandic87/7c12f244-4be8-4e78-94f8-ba87266f4032 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, "adammandic87/7c12f244-4be8-4e78-94f8-ba87266f4032") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from adammandic87/7c12f244-4be8-4e78-94f8-ba87266f4032: direct link, hf CLI and curl.
- Browser
- Download file 5.96 MB
-
https://huggingface.co/adammandic87/7c12f244-4be8-4e78-94f8-ba87266f4032/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://adammandic87/7c12f244-4be8-4e78-94f8-ba87266f4032/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/adammandic87/7c12f244-4be8-4e78-94f8-ba87266f4032/resolve/main/last-checkpoint/optimizer.pt
5.96 MB
- Xet hash:
- f95d72a0eda3ac53193bf50f1849c9931abd755f7e090259529c179d7eaca785
- Size of remote file:
- 5.96 MB
- SHA256:
- 11407487f4da3f4ab302670472ba6d2ebdff710ddcf970e2c332a9dd25dd1443
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