Instructions to use Rogashbabu/sentiment_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rogashbabu/sentiment_analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Rogashbabu/sentiment_analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Rogashbabu/sentiment_analysis") model = AutoModelForSequenceClassification.from_pretrained("Rogashbabu/sentiment_analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
af5ce59
1
Parent(s): a100797
Upload tokenizer
Browse files- tokenizer_config.json +1 -0
tokenizer_config.json
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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"never_split": null,
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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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"do_lower_case": true,
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"from_cache": true,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"never_split": null,
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