Instructions to use nhung01/f0fcc583-c1c6-46df-b638-dbf595dfa987 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung01/f0fcc583-c1c6-46df-b638-dbf595dfa987 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-2-7b-chat") model = PeftModel.from_pretrained(base_model, "nhung01/f0fcc583-c1c6-46df-b638-dbf595dfa987") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a9beacf3b51a1f263aeff01f3bc9bb1833159a97b53c93367211509adc8856f
- Size of remote file:
- 6.78 kB
- SHA256:
- 91b60f8df6f9410a464ac53c1e3d5b2dd97cc0dec093290e9805abfc3b163b32
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