Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use DayCardoso/modernbert-base-multi-head-values-context-roc_auc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DayCardoso/modernbert-base-multi-head-values-context-roc_auc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DayCardoso/modernbert-base-multi-head-values-context-roc_auc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DayCardoso/modernbert-base-multi-head-values-context-roc_auc") model = AutoModelForSequenceClassification.from_pretrained("DayCardoso/modernbert-base-multi-head-values-context-roc_auc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from DayCardoso/modernbert-base-multi-head-values-context-roc_auc: direct link, hf CLI and curl.
- Browser
- Download file 3.59 MB
-
https://huggingface.co/DayCardoso/modernbert-base-multi-head-values-context-roc_auc/resolve/main/tokenizer.json
- Command line
-
hf download hf://DayCardoso/modernbert-base-multi-head-values-context-roc_auc/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/DayCardoso/modernbert-base-multi-head-values-context-roc_auc/resolve/main/tokenizer.json
3.59 MB
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