Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use prakhars/instagram_caption_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prakhars/instagram_caption_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="prakhars/instagram_caption_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("prakhars/instagram_caption_classifier") model = AutoModelForSequenceClassification.from_pretrained("prakhars/instagram_caption_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload DistilBertForSequenceClassification
Browse files- config.json +43 -43
- pytorch_model.bin +2 -2
config.json
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{
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"_name_or_path": "
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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"dropout": 0.1,
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"hidden_dim": 3072,
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"_name_or_path": "prakhars/instagram_caption_classifier",
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "Art and Culture",
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"1": "Automotive",
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"2": "Beauty, Fashion and Lifestyle",
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"20": "Travel"
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"initializer_range": 0.02,
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"label2id": {
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"Art and Culture": 0,
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"Automotive": 1,
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"Beauty, Fashion and Lifestyle": 2,
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"Food": 10,
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"Music": 13,
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"Parenting": 14,
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"Pets": 15,
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"Photography": 16,
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"Sports": 18,
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"Technology": 19,
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"Travel": 20
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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pytorch_model.bin
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size 267911345
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