Instructions to use laquythang/2e1757fa-e7ea-4cbd-a525-25cfbc7a8444 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use laquythang/2e1757fa-e7ea-4cbd-a525-25cfbc7a8444 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("jhflow/mistral7b-lora-multi-turn-v2") model = PeftModel.from_pretrained(base_model, "laquythang/2e1757fa-e7ea-4cbd-a525-25cfbc7a8444") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6848d779a28456715598f3ebbb5b9052ab4554dc5a7f7011c04aa77ac1f4f6f3
- Size of remote file:
- 6.78 kB
- SHA256:
- be7949611575e93d2b5e50db3dfc1ab90e2b762df23a744fa28b764f5bd6127e
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