Text Classification
Transformers
Safetensors
German
electra
historical-newspapers
ocr
job-advertisements
digital-humanities
Instructions to use Var3n/jobads-identification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Var3n/jobads-identification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Var3n/jobads-identification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Var3n/jobads-identification") model = AutoModelForSequenceClassification.from_pretrained("Var3n/jobads-identification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Var3n/jobads-identification: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/Var3n/jobads-identification/resolve/main/training_args.bin
- Command line
-
hf download hf://Var3n/jobads-identification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Var3n/jobads-identification/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- da595b128003fb15fa92262b3d27e568973d3788b437988d10447c0eb3db4f73
- Size of remote file:
- 5.24 kB
- SHA256:
- deb59e22d1f815774f51cb970976aa2044a7df9ac51ad72dc21b1693d5b69f45
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