Instructions to use tryingpro/fff4bb41-fbd1-4606-80cd-29d5047ddf58 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tryingpro/fff4bb41-fbd1-4606-80cd-29d5047ddf58 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, "tryingpro/fff4bb41-fbd1-4606-80cd-29d5047ddf58") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from tryingpro/fff4bb41-fbd1-4606-80cd-29d5047ddf58: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/tryingpro/fff4bb41-fbd1-4606-80cd-29d5047ddf58/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://tryingpro/fff4bb41-fbd1-4606-80cd-29d5047ddf58/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tryingpro/fff4bb41-fbd1-4606-80cd-29d5047ddf58/resolve/main/last-checkpoint/training_args.bin
6.84 kB
- Xet hash:
- aa267979816a29def63c3c65aa084e0ea92482272be9ded3be6e6f1d38cdb140
- Size of remote file:
- 6.84 kB
- SHA256:
- 0b4e8b448262bc5882842e9b9f796b73b0a507c3edb17b7a700c8f41f766db1a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.