Instructions to use dean22029/PeoplesDailyClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dean22029/PeoplesDailyClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dean22029/PeoplesDailyClassifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dean22029/PeoplesDailyClassifier") model = AutoModelForSequenceClassification.from_pretrained("dean22029/PeoplesDailyClassifier") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- all_results.json +1 -0
- config.json +30 -3
- model.safetensors +2 -2
all_results.json
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{"eval_accuracy": 0.7609399916072178}
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config.json
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"classifier_dropout": null,
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"directionality": "bidi",
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"eos_token_id": 2,
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"finetuning_task": "sst2",
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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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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"classifier_dropout": null,
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"directionality": "bidi",
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"eos_token_id": 2,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2",
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"3": "LABEL_3",
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"12": "LABEL_12",
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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"0": 0,
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"1": 1,
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"2": 2,
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"13": 13
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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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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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size 1302194104
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