Fill-Mask
Transformers
Safetensors
English
modernbert
conflict
political-violence
event-data
political-science
domain-adaptation
long-context
Instructions to use eventdata-utd/ConfliBERT-2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eventdata-utd/ConfliBERT-2-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="eventdata-utd/ConfliBERT-2-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("eventdata-utd/ConfliBERT-2-base") model = AutoModelForMaskedLM.from_pretrained("eventdata-utd/ConfliBERT-2-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 484 Bytes
db43748 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"backend": "tokenizers",
"clean_up_tokenization_spaces": false,
"cls_token": "[CLS]",
"is_local": true,
"local_files_only": true,
"mask_token": "[MASK]",
"max_length": null,
"model_input_names": [
"input_ids",
"attention_mask"
],
"model_max_length": 8192,
"pad_to_multiple_of": null,
"pad_token": "[PAD]",
"pad_token_type_id": 0,
"padding_side": "right",
"sep_token": "[SEP]",
"tokenizer_class": "TokenizersBackend",
"unk_token": "[UNK]"
}
|