Instructions to use thangla01/a9491cfd-4149-40fa-ac9b-fb70ebdd8a11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thangla01/a9491cfd-4149-40fa-ac9b-fb70ebdd8a11 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, "thangla01/a9491cfd-4149-40fa-ac9b-fb70ebdd8a11") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 491e13732969dbffcb02ab46dd20164d728f371d94703fbe86133c9cdc42bca3
- Size of remote file:
- 6.78 kB
- SHA256:
- 5d515e349d4ecf65f4bc34c8d49f91f1844287b5a12bb88e538768a5648d0b88
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