Instructions to use blockenters/distilbert-base-uncased-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blockenters/distilbert-base-uncased-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="blockenters/distilbert-base-uncased-imdb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("blockenters/distilbert-base-uncased-imdb") model = AutoModelForSequenceClassification.from_pretrained("blockenters/distilbert-base-uncased-imdb") - Notebooks
- Google Colab
- Kaggle
Upload config
Browse files- config.json +0 -2
config.json
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"n_layers": 6,
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"output_past": true,
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"pad_token_id": 0,
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"problem_type": "single_label_classification",
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.48.2",
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"vocab_size": 30522
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}
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"n_layers": 6,
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"output_past": true,
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"pad_token_id": 0,
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"transformers_version": "4.48.2",
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"vocab_size": 30522
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}
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