Instructions to use minhnguyennnnnn/3cfe61ba-9f72-454f-bb95-3a1e3b0f9590 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use minhnguyennnnnn/3cfe61ba-9f72-454f-bb95-3a1e3b0f9590 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-instruct-v0.2") model = PeftModel.from_pretrained(base_model, "minhnguyennnnnn/3cfe61ba-9f72-454f-bb95-3a1e3b0f9590") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cade2627180caf3a6bd070bdfc1dc3bd4cdf7bf83890206085c96a1cc99cb14c
- Size of remote file:
- 6.78 kB
- SHA256:
- cb1fb02210883e8a10195a01b136a930163eec219f1069dd35e76b3620618074
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