Instructions to use alothomas/radbert-rad-verifier-single with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alothomas/radbert-rad-verifier-single with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alothomas/radbert-rad-verifier-single")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alothomas/radbert-rad-verifier-single") model = AutoModelForSequenceClassification.from_pretrained("alothomas/radbert-rad-verifier-single", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download eval/metrics.csv from alothomas/radbert-rad-verifier-single: direct link, hf CLI and curl.
- Browser
- Download file 777 Bytes
-
https://huggingface.co/alothomas/radbert-rad-verifier-single/resolve/main/eval/metrics.csv
- Command line
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hf download hf://alothomas/radbert-rad-verifier-single/eval/metrics.csv
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curl -L -o metrics.csv https://huggingface.co/alothomas/radbert-rad-verifier-single/resolve/main/eval/metrics.csv
777 Bytes
| variant,point_accuracy,point_f1_macro,point_f1_micro,point_mcc,point_auroc,point_auprc,accuracy_mean,accuracy_lo95,accuracy_hi95,f1_macro_mean,f1_macro_lo95,f1_macro_hi95,f1_micro_mean,f1_micro_lo95,f1_micro_hi95,mcc_mean,mcc_lo95,mcc_hi95,auroc_mean,auroc_lo95,auroc_hi95,auprc_mean,auprc_lo95,auprc_hi95 | |
| radbert-single,0.7385665529010239,0.7361570563686592,0.7385665529010239,0.47508349110926684,0.8319447403536708,0.8204006514609125,0.7384068259385665,0.715358361774744,0.7604095563139932,0.735849955113505,0.7124265010267299,0.7576361788876373,0.7384068259385665,0.7153583617747441,0.7604095563139931,0.4746827620882819,0.42931468337157186,0.5181940828509641,0.8317784108880514,0.8104457050524878,0.8517814681286039,0.8206129490340163,0.7915604576396064,0.8475091223203132 | |