Instructions to use phungkhaccuong/32d80887-0374-43a4-bac6-176065c15fda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use phungkhaccuong/32d80887-0374-43a4-bac6-176065c15fda with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("MNC-Jihun/Mistral-7B-AO-u0.5-b2-ver0.4") model = PeftModel.from_pretrained(base_model, "phungkhaccuong/32d80887-0374-43a4-bac6-176065c15fda") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8414ea95d2833fdb6d4746991e7b3245ee57a8eab882cf421250ce979c63e898
- Size of remote file:
- 6.78 kB
- SHA256:
- 6825a90782e4d6c1aff5465c1b611126e3bec8a7e140453f234638c2130e61d8
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