Instructions to use vdos/702daad2-31e6-4ed8-9647-43c4a17482bb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vdos/702daad2-31e6-4ed8-9647-43c4a17482bb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2b-it") model = PeftModel.from_pretrained(base_model, "vdos/702daad2-31e6-4ed8-9647-43c4a17482bb") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from vdos/702daad2-31e6-4ed8-9647-43c4a17482bb: direct link, hf CLI and curl.
- Browser
- Download file 314 MB
-
https://huggingface.co/vdos/702daad2-31e6-4ed8-9647-43c4a17482bb/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://vdos/702daad2-31e6-4ed8-9647-43c4a17482bb/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/vdos/702daad2-31e6-4ed8-9647-43c4a17482bb/resolve/main/last-checkpoint/optimizer.pt
314 MB
- Xet hash:
- c3527b1b8f25ef7ea03b18738dff92e669e23b43cec59612942ea94edc4befaa
- Size of remote file:
- 314 MB
- SHA256:
- cead1b8cabc7e38bdb84692fb5323e8f49fe4c5fb8df06fa5b40046af2e4bbb7
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