Instructions to use BhandariShivam/gpt2-IMDB-sentiment-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BhandariShivam/gpt2-IMDB-sentiment-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BhandariShivam/gpt2-IMDB-sentiment-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BhandariShivam/gpt2-IMDB-sentiment-classifier") model = AutoModelForSequenceClassification.from_pretrained("BhandariShivam/gpt2-IMDB-sentiment-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- tokenizer.json +0 -0
- tokenizer_config.json +13 -0
tokenizer.json
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"backend": "tokenizers",
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"bos_token": "<|endoftext|>",
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"eos_token": "<|endoftext|>",
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"errors": "replace",
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"is_local": false,
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"local_files_only": false,
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"model_max_length": 1024,
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"pad_token": "<|endoftext|>",
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"tokenizer_class": "GPT2Tokenizer",
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"unk_token": "<|endoftext|>"
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}
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