Instructions to use HKReporter/ECTEL-2025-llama3-fold5-CU3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use HKReporter/ECTEL-2025-llama3-fold5-CU3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b-Instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "HKReporter/ECTEL-2025-llama3-fold5-CU3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0abe1116705daf85309b97c30297f10b2a79921e2a540c6acfb242a2e89243b
- Size of remote file:
- 1.47 kB
- SHA256:
- 985fd84033fefa6bef30048f534b27083cc9fe9b4a33b4ce200a21913ea512f4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.