Instructions to use MBuechel/TTP_SOK with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MBuechel/TTP_SOK with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MBuechel/TTP_SOK")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MBuechel/TTP_SOK", device_map="auto") - Notebooks
- Google Colab
- Kaggle
TTP_SOK / Classification /data_augmentation /400_tram_artificial_FacebookAI-roberta-large /tokenizer.json
Download Classification/data_augmentation/400_tram_artificial_FacebookAI-roberta-large/tokenizer.json from MBuechel/TTP_SOK: direct link, hf CLI and curl.
- Browser
- Download file 3.56 MB
-
https://huggingface.co/MBuechel/TTP_SOK/resolve/main/Classification/data_augmentation/400_tram_artificial_FacebookAI-roberta-large/tokenizer.json
- Command line
-
hf download hf://MBuechel/TTP_SOK/Classification/data_augmentation/400_tram_artificial_FacebookAI-roberta-large/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/MBuechel/TTP_SOK/resolve/main/Classification/data_augmentation/400_tram_artificial_FacebookAI-roberta-large/tokenizer.json
3.56 MB
File too large to display, you can check the raw version instead.