Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use swapnasa/danish-intent-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use swapnasa/danish-intent-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="swapnasa/danish-intent-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("swapnasa/danish-intent-classifier") model = AutoModelForSequenceClassification.from_pretrained("swapnasa/danish-intent-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from swapnasa/danish-intent-classifier: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/swapnasa/danish-intent-classifier/resolve/main/tokenizer.json
- Command line
-
hf download hf://swapnasa/danish-intent-classifier/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/swapnasa/danish-intent-classifier/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 30b23f71459ecebcf68e355d612f0a9227cec02986dc39efb3fd136377f8707f
- Size of remote file:
- 17.1 MB
- SHA256:
- 02bd578944893325af3792a8974700da7763f7689b0959c6a9ac655c80a3824c
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