Instructions to use dada22231/7deb2616-685c-4bbf-8ec9-faa8d781e17a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/7deb2616-685c-4bbf-8ec9-faa8d781e17a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "dada22231/7deb2616-685c-4bbf-8ec9-faa8d781e17a") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from dada22231/7deb2616-685c-4bbf-8ec9-faa8d781e17a: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/dada22231/7deb2616-685c-4bbf-8ec9-faa8d781e17a/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://dada22231/7deb2616-685c-4bbf-8ec9-faa8d781e17a/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dada22231/7deb2616-685c-4bbf-8ec9-faa8d781e17a/resolve/main/last-checkpoint/training_args.bin
6.84 kB
- Xet hash:
- 566112c44c56dfd21e4a4e90af262a1ea8481b191190bd19b45e488ae6b1c62c
- Size of remote file:
- 6.84 kB
- SHA256:
- 61690bf6feaa765a305c618bf645a668a217b4f6a0572f17f580782caa79a925
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.