Instructions to use nhung01/de4b746d-5809-4184-9daf-64e8308b0463 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung01/de4b746d-5809-4184-9daf-64e8308b0463 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen1.5-14B-Chat") model = PeftModel.from_pretrained(base_model, "nhung01/de4b746d-5809-4184-9daf-64e8308b0463") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98beaa2d873b2e408c6c87a8ae33d0d24c82d48c2f1feae1ea1fa05f567bd544
- Size of remote file:
- 250 MB
- SHA256:
- 66e043e609a8528065bb81d25b96b76506a2fd8a88ae2ec5a332a180abdf753e
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