Instructions to use FlowRank/mailSort with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FlowRank/mailSort with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FlowRank/mailSort")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FlowRank/mailSort", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,907 Bytes
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"activation": "gelu",
"architectures": [
"DistilBertForSequenceClassification"
],
"attention_dropout": 0.1,
"bos_token_id": null,
"dim": 768,
"dropout": 0.1,
"dtype": "float32",
"eos_token_id": null,
"hidden_dim": 3072,
"id2label": {
"0": "family_not_urgent",
"1": "family_urgent",
"2": "finance_not_urgent",
"3": "finance_urgent",
"4": "games_not_urgent",
"5": "games_urgent",
"6": "human resources_not_urgent",
"7": "human resources_urgent",
"8": "medical_not_urgent",
"9": "medical_urgent",
"10": "pets_not_urgent",
"11": "pets_urgent",
"12": "school_not_urgent",
"13": "school_urgent",
"14": "software engineering_not_urgent",
"15": "software engineering_urgent",
"16": "sport_not_urgent",
"17": "sport_urgent",
"18": "work/airbus_not_urgent",
"19": "work/airbus_urgent"
},
"initializer_range": 0.02,
"label2id": {
"family_not_urgent": 0,
"family_urgent": 1,
"finance_not_urgent": 2,
"finance_urgent": 3,
"games_not_urgent": 4,
"games_urgent": 5,
"human resources_not_urgent": 6,
"human resources_urgent": 7,
"medical_not_urgent": 8,
"medical_urgent": 9,
"pets_not_urgent": 10,
"pets_urgent": 11,
"school_not_urgent": 12,
"school_urgent": 13,
"software engineering_not_urgent": 14,
"software engineering_urgent": 15,
"sport_not_urgent": 16,
"sport_urgent": 17,
"work/airbus_not_urgent": 18,
"work/airbus_urgent": 19
},
"max_position_embeddings": 512,
"model_type": "distilbert",
"n_heads": 12,
"n_layers": 6,
"pad_token_id": 0,
"problem_type": "single_label_classification",
"qa_dropout": 0.1,
"seq_classif_dropout": 0.2,
"sinusoidal_pos_embds": false,
"tie_weights_": true,
"tie_word_embeddings": true,
"transformers_version": "5.8.0",
"use_cache": false,
"vocab_size": 30522
}
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