Instructions to use aleegis12/1192696c-aa12-4e64-b0fe-dcccc7dd37e3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aleegis12/1192696c-aa12-4e64-b0fe-dcccc7dd37e3 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, "aleegis12/1192696c-aa12-4e64-b0fe-dcccc7dd37e3") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from aleegis12/1192696c-aa12-4e64-b0fe-dcccc7dd37e3: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/aleegis12/1192696c-aa12-4e64-b0fe-dcccc7dd37e3/resolve/main/training_args.bin
- Command line
-
hf download hf://aleegis12/1192696c-aa12-4e64-b0fe-dcccc7dd37e3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/aleegis12/1192696c-aa12-4e64-b0fe-dcccc7dd37e3/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 57f2fe3812d57945a7859f1fdcb7cc07a243dd42ba990560438f7648bd7d5a6b
- Size of remote file:
- 6.84 kB
- SHA256:
- fc1ea9f1f7647ad514bbcaf55ef782dcfec14c32757c97f9541290a76a036241
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