Instructions to use mennasherif/mennas_second_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mennasherif/mennas_second_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mennasherif/mennas_second_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mennasherif/mennas_second_model") model = AutoModelForSequenceClassification.from_pretrained("mennasherif/mennas_second_model") - Notebooks
- Google Colab
- Kaggle
File size: 931 Bytes
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"id2label": {
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"layer_norm_eps": 1e-12,
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"model_type": "bert",
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"pre_trained": "",
"problem_type": "single_label_classification",
"structure": [],
"tie_word_embeddings": true,
"transformers_version": "5.0.0",
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}
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