Token Classification
Transformers
Safetensors
deberta-v2
political-science
multilingual
deberta
group-appeals
Instructions to use rwillh11/mdberta-token-bilingual-noContext_Enhanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rwillh11/mdberta-token-bilingual-noContext_Enhanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rwillh11/mdberta-token-bilingual-noContext_Enhanced")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rwillh11/mdberta-token-bilingual-noContext_Enhanced") model = AutoModelForTokenClassification.from_pretrained("rwillh11/mdberta-token-bilingual-noContext_Enhanced", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spm.model from rwillh11/mdberta-token-bilingual-noContext_Enhanced: direct link, hf CLI and curl.
- Browser
- Download file 4.31 MB
-
https://huggingface.co/rwillh11/mdberta-token-bilingual-noContext_Enhanced/resolve/main/spm.model
- Command line
-
hf download hf://rwillh11/mdberta-token-bilingual-noContext_Enhanced/spm.model
-
curl -L -o spm.model https://huggingface.co/rwillh11/mdberta-token-bilingual-noContext_Enhanced/resolve/main/spm.model
4.31 MB
- Xet hash:
- c4b914ec5ab295fbee3b0e0fe62f22febb3c09d34dd3778745e0de034a76df33
- Size of remote file:
- 4.31 MB
- SHA256:
- 13c8d666d62a7bc4ac8f040aab68e942c861f93303156cc28f5c7e885d86d6e3
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