Instructions to use Azie88/Coachella_sentiment_analysis_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Azie88/Coachella_sentiment_analysis_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Azie88/Coachella_sentiment_analysis_roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Azie88/Coachella_sentiment_analysis_roberta") model = AutoModelForSequenceClassification.from_pretrained("Azie88/Coachella_sentiment_analysis_roberta") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- tokenizer.json +0 -0
- tokenizer_config.json +2 -1
tokenizer.json
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tokenizer_config.json
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"clean_up_tokenization_spaces":
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"cls_token": "<s>",
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"eos_token": "</s>",
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"errors": "replace",
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"mask_token": "<mask>",
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<pad>",
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"clean_up_tokenization_spaces": false,
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"cls_token": "<s>",
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"eos_token": "</s>",
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"errors": "replace",
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"extra_special_tokens": {},
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"mask_token": "<mask>",
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<pad>",
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