Instructions to use tarabukinivan/d7d0741c-b0e3-40c8-82c3-1dec958d7df0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tarabukinivan/d7d0741c-b0e3-40c8-82c3-1dec958d7df0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b") model = PeftModel.from_pretrained(base_model, "tarabukinivan/d7d0741c-b0e3-40c8-82c3-1dec958d7df0") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tarabukinivan/d7d0741c-b0e3-40c8-82c3-1dec958d7df0: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/tarabukinivan/d7d0741c-b0e3-40c8-82c3-1dec958d7df0/resolve/main/training_args.bin
- Command line
-
hf download hf://tarabukinivan/d7d0741c-b0e3-40c8-82c3-1dec958d7df0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tarabukinivan/d7d0741c-b0e3-40c8-82c3-1dec958d7df0/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 8e6f69fd7c8f21763b129bb206c004707e4a482323e35cde188f2e51e9872e83
- Size of remote file:
- 6.78 kB
- SHA256:
- efa1daa0b932adddac82e24ab8f7b93839d287cb448541195b5c06301bbf62e4
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