Text Classification
Transformers
TensorBoard
Safetensors
English
modernbert
Generated from Trainer
topic-detection
web-content-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use davanstrien/ModernBERT-web-topics-1m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/ModernBERT-web-topics-1m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davanstrien/ModernBERT-web-topics-1m")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davanstrien/ModernBERT-web-topics-1m") model = AutoModelForSequenceClassification.from_pretrained("davanstrien/ModernBERT-web-topics-1m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from davanstrien/ModernBERT-web-topics-1m: direct link, hf CLI and curl.
- Browser
- Download file 3.58 MB
-
https://huggingface.co/davanstrien/ModernBERT-web-topics-1m/resolve/main/tokenizer.json
- Command line
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hf download hf://davanstrien/ModernBERT-web-topics-1m/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/davanstrien/ModernBERT-web-topics-1m/resolve/main/tokenizer.json
3.58 MB
File too large to display, you can check the raw version instead.