Instructions to use Aivesa/c61150d9-1501-429d-bbbf-bcd9cf65c7a1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Aivesa/c61150d9-1501-429d-bbbf-bcd9cf65c7a1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("dunzhang/stella_en_1.5B_v5") model = PeftModel.from_pretrained(base_model, "Aivesa/c61150d9-1501-429d-bbbf-bcd9cf65c7a1") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/rng_state.pth from Aivesa/c61150d9-1501-429d-bbbf-bcd9cf65c7a1: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/Aivesa/c61150d9-1501-429d-bbbf-bcd9cf65c7a1/resolve/main/last-checkpoint/rng_state.pth
- Command line
-
hf download hf://Aivesa/c61150d9-1501-429d-bbbf-bcd9cf65c7a1/last-checkpoint/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/Aivesa/c61150d9-1501-429d-bbbf-bcd9cf65c7a1/resolve/main/last-checkpoint/rng_state.pth
14.2 kB
- Xet hash:
- 863ad94cc1eb70ad753457f8a6b02c4ddf1a15d514798d252b34b9a8f7a624ed
- Size of remote file:
- 14.2 kB
- SHA256:
- d57765ccdbd3b79c135f681da7122fdba173117294579537d75e298a46d06671
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