Instructions to use RashidNLP/German-Text-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RashidNLP/German-Text-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RashidNLP/German-Text-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RashidNLP/German-Text-Classification") model = AutoModelForSequenceClassification.from_pretrained("RashidNLP/German-Text-Classification") - Notebooks
- Google Colab
- Kaggle
File size: 451 Bytes
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"mask_token": {
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"lstrip": true,
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"rstrip": false,
"single_word": false
},
"model_max_length": 512,
"name_or_path": "xlm-roberta-base",
"pad_token": "<pad>",
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"tokenizer_class": "XLMRobertaTokenizer",
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}
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