Token Classification
Transformers
Safetensors
English
roberta
sequence-labeling
political-science
social-groups
parliamentary-debates
Instructions to use maxwlnd/roberta_group_mention_detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maxwlnd/roberta_group_mention_detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="maxwlnd/roberta_group_mention_detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("maxwlnd/roberta_group_mention_detector") model = AutoModelForTokenClassification.from_pretrained("maxwlnd/roberta_group_mention_detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
update model card
MaximilianWeilanda99d025 -
update model card
MaximilianWeiland9554ad4 -
add model_card
MaximilianWeiland52b4e00
-
Replace pytorch_model.bin with model.safetensors, add tokenizer files
MaximilianWeiland645618d
-
updated config file to include label2id and id2label
MaximilianWeiland2df5575 -
updated config
MaximilianWeilandae07f36 -
updated max position embeddings in config
MaximilianWeiland13f7872 -
updated config file
MaximilianWeilandf4bccc0 -
changed file name to config
MaximilianWeiland6578c8c -
changed vocab size
MaximilianWeiland312efd9 -
changed bin model file name
MaximilianWeiland9228645 -
Rename model weights to pytorch_model.bin
MaximilianWeiland57a4f8a -
Add RoBERTa token classification model
MaximilianWeilandb7488a4 -
initial commit
Verified signatured565b67