Instructions to use dzanbek/d88783a6-4c53-475a-8545-bf69a0286e0c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/d88783a6-4c53-475a-8545-bf69a0286e0c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("scb10x/llama-3-typhoon-v1.5-8b-instruct") model = PeftModel.from_pretrained(base_model, "dzanbek/d88783a6-4c53-475a-8545-bf69a0286e0c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 046e75da0b99fa65e86eea8c76524888740a85540bd663f3568051f7bb245c47
- Size of remote file:
- 6.78 kB
- SHA256:
- 2f191001f96eaa6dc6d2983323b931f28cad73c21aede8fff03b423965064c7c
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