Text Classification
Transformers
TensorFlow
xlm-roberta
generated_from_keras_callback
text-embeddings-inference
Instructions to use cruiser/roberta_tensorflow_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cruiser/roberta_tensorflow_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cruiser/roberta_tensorflow_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cruiser/roberta_tensorflow_test") model = AutoModelForSequenceClassification.from_pretrained("cruiser/roberta_tensorflow_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 643 Bytes
e280650 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"bos_token": "<s>",
"cls_token": "<s>",
"eos_token": "</s>",
"mask_token": {
"__type": "AddedToken",
"content": "<mask>",
"lstrip": true,
"normalized": true,
"rstrip": false,
"single_word": false
},
"name_or_path": "cardiffnlp/twitter-xlm-roberta-base-sentiment",
"pad_token": "<pad>",
"sep_token": "</s>",
"sp_model_kwargs": {},
"special_tokens_map_file": "/root/.cache/huggingface/transformers/6654a835c284613a15c3b583fce96f417606b95fab5ef47cc3da33de8ac237b6.0dc5b1041f62041ebbd23b1297f2f573769d5c97d8b7c28180ec86b8f6185aa8",
"tokenizer_class": "XLMRobertaTokenizer",
"unk_token": "<unk>"
}
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