Instructions to use JanSt/gbert-base_DA_sosec-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JanSt/gbert-base_DA_sosec-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JanSt/gbert-base_DA_sosec-sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JanSt/gbert-base_DA_sosec-sentiment") model = AutoModelForSequenceClassification.from_pretrained("JanSt/gbert-base_DA_sosec-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from JanSt/gbert-base_DA_sosec-sentiment: direct link, hf CLI and curl.
- Browser
- Download file 729 kB
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https://huggingface.co/JanSt/gbert-base_DA_sosec-sentiment/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
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hf download hf://JanSt/gbert-base_DA_sosec-sentiment@refs/pr/1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/JanSt/gbert-base_DA_sosec-sentiment/resolve/refs%2Fpr%2F1/tokenizer.json
729 kB
File too large to display, you can check the raw version instead.