Instructions to use eeeebbb2/d48e42af-7fb4-4b45-91be-78cd06b291f0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/d48e42af-7fb4-4b45-91be-78cd06b291f0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.1-Storm-8B") model = PeftModel.from_pretrained(base_model, "eeeebbb2/d48e42af-7fb4-4b45-91be-78cd06b291f0") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/rng_state_2.pth from eeeebbb2/d48e42af-7fb4-4b45-91be-78cd06b291f0: direct link, hf CLI and curl.
- Browser
- Download file 15 kB
-
https://huggingface.co/eeeebbb2/d48e42af-7fb4-4b45-91be-78cd06b291f0/resolve/main/last-checkpoint/rng_state_2.pth
- Command line
-
hf download hf://eeeebbb2/d48e42af-7fb4-4b45-91be-78cd06b291f0/last-checkpoint/rng_state_2.pth
-
curl -L -o rng_state_2.pth https://huggingface.co/eeeebbb2/d48e42af-7fb4-4b45-91be-78cd06b291f0/resolve/main/last-checkpoint/rng_state_2.pth
15 kB
- Xet hash:
- 8dbbc840b9c503825d93a9a0672cdd95b976a682e3c763e35d4b1cea4553d380
- Size of remote file:
- 15 kB
- SHA256:
- 2f26fd9e04dc5f47e9d08cd7d34cf8c50485ee8b0edc5eb41ce72915b38cae21
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