Instructions to use nhung01/c7b3afed-dce2-40c7-bed1-fc4a1cd4fe7e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung01/c7b3afed-dce2-40c7-bed1-fc4a1cd4fe7e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Meta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "nhung01/c7b3afed-dce2-40c7-bed1-fc4a1cd4fe7e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92487d26cdcacfe9f5a2c599b1c7297a7868c01ebce43b1ca78e512099d103b5
- Size of remote file:
- 6.78 kB
- SHA256:
- c4f40724aa6dd46328162fc229a29fd500e9e5846612c0016bba40427837f80a
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