Instructions to use dzanbek/507584e4-5391-4dea-9e35-556b4abc0fa1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/507584e4-5391-4dea-9e35-556b4abc0fa1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-random-GemmaForCausalLM") model = PeftModel.from_pretrained(base_model, "dzanbek/507584e4-5391-4dea-9e35-556b4abc0fa1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15f6da91eff7915aebe3175ad1429ba74a94c9bef375849b264fc799c5982241
- Size of remote file:
- 6.78 kB
- SHA256:
- 50da0cdbe50ac03af0c1ae36584daa095ea9379e600fa67b7afab0c23469d8f2
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