Instructions to use dada22231/6bb2c487-2992-441b-90d1-b2fec57e5176 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/6bb2c487-2992-441b-90d1-b2fec57e5176 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Mistral-7B") model = PeftModel.from_pretrained(base_model, "dada22231/6bb2c487-2992-441b-90d1-b2fec57e5176") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/rng_state_2.pth from dada22231/6bb2c487-2992-441b-90d1-b2fec57e5176: direct link, hf CLI and curl.
- Browser
- Download file 15 kB
-
https://huggingface.co/dada22231/6bb2c487-2992-441b-90d1-b2fec57e5176/resolve/main/last-checkpoint/rng_state_2.pth
- Command line
-
hf download hf://dada22231/6bb2c487-2992-441b-90d1-b2fec57e5176/last-checkpoint/rng_state_2.pth
-
curl -L -o rng_state_2.pth https://huggingface.co/dada22231/6bb2c487-2992-441b-90d1-b2fec57e5176/resolve/main/last-checkpoint/rng_state_2.pth
15 kB
- Xet hash:
- 188d17899d170153bd11e39ddc68d0ec7cd36afe72bc9a55f0505f5ab1769089
- Size of remote file:
- 15 kB
- SHA256:
- db2aea2d54edf46a5ace03fc4738c448a211ba730c21c0057f586b4b1590164e
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