Instructions to use nhung03/bd08913d-aff9-4e52-9536-39d293fd521b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung03/bd08913d-aff9-4e52-9536-39d293fd521b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Orenguteng/Llama-3-8B-Lexi-Uncensored") model = PeftModel.from_pretrained(base_model, "nhung03/bd08913d-aff9-4e52-9536-39d293fd521b") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nhung03/bd08913d-aff9-4e52-9536-39d293fd521b: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/nhung03/bd08913d-aff9-4e52-9536-39d293fd521b/resolve/main/training_args.bin
- Command line
-
hf download hf://nhung03/bd08913d-aff9-4e52-9536-39d293fd521b/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nhung03/bd08913d-aff9-4e52-9536-39d293fd521b/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 267ef6c2c7ec1496e51c8dc73ed6857bb3686618c6408e8ea07134da0abba1e5
- Size of remote file:
- 6.78 kB
- SHA256:
- 70c90f837d1d17a27af78e62dc78a2198546aee06ff9aee3fdd1933716d6cc2d
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