Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use tinutmap/ai-browsing-categories-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tinutmap/ai-browsing-categories-text with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tinutmap/ai-browsing-categories-text")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tinutmap/ai-browsing-categories-text") model = AutoModelForSequenceClassification.from_pretrained("tinutmap/ai-browsing-categories-text", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,266 Bytes
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"activation": "gelu",
"architectures": [
"DistilBertForSequenceClassification"
],
"attention_dropout": 0.1,
"dim": 768,
"dropout": 0.1,
"hidden_dim": 3072,
"id2label": {
"0": "Accessories",
"1": "Architectural",
"2": "Desking",
"3": "Lighting",
"4": "Seating",
"5": "Space Division",
"6": "Storage",
"7": "Tables",
"8": "Unknown",
"9": "Workspaces"
},
"initializer_range": 0.02,
"label2id": {
"Accessories": 0,
"Architectural": 1,
"Desking": 2,
"Lighting": 3,
"Seating": 4,
"Space Division": 5,
"Storage": 6,
"Tables": 7,
"Unknown": 8,
"Workspaces": 9
},
"label_vs_category_id": {
"Accessories": 1,
"Architectural": 2,
"Desking": 5,
"Lighting": 8,
"Seating": 11,
"Space Division": 12,
"Storage": 13,
"Tables": 15,
"Unknown": 19,
"Workspaces": 20
},
"max_position_embeddings": 512,
"model_type": "distilbert",
"n_heads": 12,
"n_layers": 6,
"pad_token_id": 0,
"problem_type": "multi_label_classification",
"qa_dropout": 0.1,
"seq_classif_dropout": 0.2,
"sinusoidal_pos_embds": false,
"tie_weights_": true,
"torch_dtype": "float32",
"transformers_version": "4.53.3",
"vocab_size": 30522
}
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