Instructions to use dimasik2987/9f20610d-d76f-414d-9e50-134be458ed3e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik2987/9f20610d-d76f-414d-9e50-134be458ed3e 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, "dimasik2987/9f20610d-d76f-414d-9e50-134be458ed3e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 334ba71862764a86ba5dff4cc06b590d613f644609a5abe690a0a08e4ee46513
- Size of remote file:
- 336 MB
- SHA256:
- acb9c8d9e4f18c9e0c19bcbbf01a8629bd83628144e8d6e6c4ed4144a47208d9
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