Instructions to use cilorku/d27ec5d2-bb38-461d-b584-23122f0f0613 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cilorku/d27ec5d2-bb38-461d-b584-23122f0f0613 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-instruct-v0.3") model = PeftModel.from_pretrained(base_model, "cilorku/d27ec5d2-bb38-461d-b584-23122f0f0613") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from cilorku/d27ec5d2-bb38-461d-b584-23122f0f0613: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/cilorku/d27ec5d2-bb38-461d-b584-23122f0f0613/resolve/main/training_args.bin
- Command line
-
hf download hf://cilorku/d27ec5d2-bb38-461d-b584-23122f0f0613/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/cilorku/d27ec5d2-bb38-461d-b584-23122f0f0613/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 782c08663fffb5b9cc0dcbb05248a65c15284a8e13f6a6b1bc43df97e229ba6f
- Size of remote file:
- 6.84 kB
- SHA256:
- 43e8d279957725c752374a01c4f0662c4627e10dd13096efc074213087310bfd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.