Instructions to use adammandic87/4e083127-f89f-4cd5-8955-22c2c6da80f8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use adammandic87/4e083127-f89f-4cd5-8955-22c2c6da80f8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Nous-Capybara-7B-V1") model = PeftModel.from_pretrained(base_model, "adammandic87/4e083127-f89f-4cd5-8955-22c2c6da80f8") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from adammandic87/4e083127-f89f-4cd5-8955-22c2c6da80f8: direct link, hf CLI and curl.
- Browser
- Download file 41.1 MB
-
https://huggingface.co/adammandic87/4e083127-f89f-4cd5-8955-22c2c6da80f8/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://adammandic87/4e083127-f89f-4cd5-8955-22c2c6da80f8/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/adammandic87/4e083127-f89f-4cd5-8955-22c2c6da80f8/resolve/main/last-checkpoint/optimizer.pt
41.1 MB
- Xet hash:
- 9b64a55699078422de94ba3cee2c14a90e06759ab808a44abd085fa2831e0b07
- Size of remote file:
- 41.1 MB
- SHA256:
- a096f930017b2cc6ca9f4453405747a76258ade452c58dcd9be9992e9b0e8145
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