Instructions to use tarabukinivan/1b15de78-1711-4590-8b04-253fd3541681 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tarabukinivan/1b15de78-1711-4590-8b04-253fd3541681 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama-chat") model = PeftModel.from_pretrained(base_model, "tarabukinivan/1b15de78-1711-4590-8b04-253fd3541681") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tarabukinivan/1b15de78-1711-4590-8b04-253fd3541681: direct link, hf CLI and curl.
- Browser
- Download file 6.71 kB
-
https://huggingface.co/tarabukinivan/1b15de78-1711-4590-8b04-253fd3541681/resolve/main/training_args.bin
- Command line
-
hf download hf://tarabukinivan/1b15de78-1711-4590-8b04-253fd3541681/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tarabukinivan/1b15de78-1711-4590-8b04-253fd3541681/resolve/main/training_args.bin
6.71 kB
- Xet hash:
- db401c0dd0599d96a4efec18eb73f469d388862133791db3ee4eb203f3656411
- Size of remote file:
- 6.71 kB
- SHA256:
- 8dec60960cb39de65862292f8ff27a6d3f6933f0d2406b05001281f8bd99234f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.