Instructions to use TungLe7661/test-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TungLe7661/test-trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TungLe7661/test-trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TungLe7661/test-trainer") model = AutoModelForSequenceClassification.from_pretrained("TungLe7661/test-trainer") - Notebooks
- Google Colab
- Kaggle
Upload config
Browse files- config.json +10 -10
config.json
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "1
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"1": "2
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "1",
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"1": "2",
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"2": "3",
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"3": "4",
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"4": "5"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"1": "0",
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"2": "1",
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"3": "2",
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"4": "3",
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"5": "4"
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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