Instructions to use 5cean/seoul_works2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 5cean/seoul_works2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="5cean/seoul_works2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("5cean/seoul_works2") model = AutoModelForSequenceClassification.from_pretrained("5cean/seoul_works2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from 5cean/seoul_works2: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/5cean/seoul_works2/resolve/main/training_args.bin
- Command line
-
hf download hf://5cean/seoul_works2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/5cean/seoul_works2/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- c2d7fed72ae4bf6886ccf76ecab6ca2925423b9fc540aa97f3eccb67e6d54c08
- Size of remote file:
- 5.18 kB
- SHA256:
- 41cb3f6b616498c2bcf2222de8801595b22d6d1ac86fa1bb7ae9792a8d68331a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.