Instructions to use tarabukinivan/d81c2d6b-ad6c-4d53-bfc2-00eaeaf1711f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tarabukinivan/d81c2d6b-ad6c-4d53-bfc2-00eaeaf1711f 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, "tarabukinivan/d81c2d6b-ad6c-4d53-bfc2-00eaeaf1711f") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa7230d9c59fc943ea453cf9eec8043361746c4916b2e95106e8c27a90018fe0
- Size of remote file:
- 84 MB
- SHA256:
- e16dae42cb3aeba95e87beb59853d91c770f77765b851685d4f495fce67a8650
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