Instructions to use abaddon182/9902becd-9a95-4997-a536-1254a8265242 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use abaddon182/9902becd-9a95-4997-a536-1254a8265242 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, "abaddon182/9902becd-9a95-4997-a536-1254a8265242") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc2a4c948b386741c357633998dba98580d64917aa3560c17a2dadb8aefb32cc
- Size of remote file:
- 671 MB
- SHA256:
- a5697a219c594be88ba24829c0f11296aed7507cd2cf9d491c27caeedd452eb6
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