Instructions to use mamung/5c36bf90-833a-4aa9-996b-95dea707aa90 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mamung/5c36bf90-833a-4aa9-996b-95dea707aa90 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "mamung/5c36bf90-833a-4aa9-996b-95dea707aa90") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f89c80de43c3b181081dbe136bc9a5b9838899111c4705e0e7cd32d60f112d86
- Size of remote file:
- 6.84 kB
- SHA256:
- 29b31b3a945209eb6a7a024ec61ff6fb6b539b48188a0b4361f8b98ab13b87fb
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