Instructions to use nttx/e6f94a75-b9d0-44ee-b02e-2ce58469a623 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nttx/e6f94a75-b9d0-44ee-b02e-2ce58469a623 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "nttx/e6f94a75-b9d0-44ee-b02e-2ce58469a623") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from nttx/e6f94a75-b9d0-44ee-b02e-2ce58469a623: direct link, hf CLI and curl.
- Browser
- Download file 204 kB
-
https://huggingface.co/nttx/e6f94a75-b9d0-44ee-b02e-2ce58469a623/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://nttx/e6f94a75-b9d0-44ee-b02e-2ce58469a623/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/nttx/e6f94a75-b9d0-44ee-b02e-2ce58469a623/resolve/main/last-checkpoint/optimizer.pt
204 kB
- Xet hash:
- 317001b7ef5db74b825e975723817aef8b5386d855ac894866798c7bca67aec4
- Size of remote file:
- 204 kB
- SHA256:
- cf11943cff04c02a0b28adaeb360c33dab52c123cf72bd75608ebb10f8d1bea8
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