Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use lvwerra/distilbert-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lvwerra/distilbert-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lvwerra/distilbert-imdb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lvwerra/distilbert-imdb") model = AutoModelForSequenceClassification.from_pretrained("lvwerra/distilbert-imdb") - Inference
- Notebooks
- Google Colab
- Kaggle
fix label mapping
Browse files- config.json +4 -4
config.json
CHANGED
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@@ -9,13 +9,13 @@
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "
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"1": "
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},
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"initializer_range": 0.02,
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"label2id": {
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"
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"
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "neg",
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"1": "pos"
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},
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"initializer_range": 0.02,
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"label2id": {
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"neg": 0,
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"pos": 1
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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