Instructions to use dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/rng_state_1.pth from dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040: direct link, hf CLI and curl.
- Browser
- Download file 15 kB
-
https://huggingface.co/dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040/resolve/main/last-checkpoint/rng_state_1.pth
- Command line
-
hf download hf://dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040/last-checkpoint/rng_state_1.pth
-
curl -L -o rng_state_1.pth https://huggingface.co/dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040/resolve/main/last-checkpoint/rng_state_1.pth
15 kB
- Xet hash:
- 62cac4b4b1084294b0dd819698fb3d351c50ca855fdd32839f77bc172c5235b4
- Size of remote file:
- 15 kB
- SHA256:
- 28a4b4d57892f6e828e7c52205c0a5a3a73a446e080c8ab10c68397041b31767
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