Text Classification
Transformers
Safetensors
Russian
customer-support
hierarchical-classification
mps
minilm
Instructions to use ZenMan67/support-ticket-classifiers-minilm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZenMan67/support-ticket-classifiers-minilm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ZenMan67/support-ticket-classifiers-minilm")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ZenMan67/support-ticket-classifiers-minilm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,562 Bytes
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"task": "handler",
"base_model": "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",
"architecture": "sentence_pooling_plus_linear",
"pooling": "mean",
"hidden_size": 384,
"num_labels": 3,
"labels": [
"auto",
"human",
"llm"
],
"max_length": 64,
"dropout": 0.2,
"encoder_config": {
"transformers_version": "5.14.1",
"architectures": [
"BertModel"
],
"output_hidden_states": false,
"return_dict": true,
"dtype": null,
"chunk_size_feed_forward": 0,
"is_encoder_decoder": false,
"id2label": {
"0": "LABEL_0",
"1": "LABEL_1"
},
"label2id": {
"LABEL_0": 0,
"LABEL_1": 1
},
"problem_type": null,
"vocab_size": 250037,
"hidden_size": 384,
"num_hidden_layers": 12,
"num_attention_heads": 12,
"intermediate_size": 1536,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"attention_probs_dropout_prob": 0.1,
"max_position_embeddings": 512,
"type_vocab_size": 2,
"initializer_range": 0.02,
"layer_norm_eps": 1e-12,
"pad_token_id": 0,
"use_cache": true,
"classifier_dropout": null,
"is_decoder": false,
"add_cross_attention": false,
"bos_token_id": null,
"eos_token_id": null,
"tie_word_embeddings": true,
"_name_or_path": "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",
"gradient_checkpointing": false,
"model_type": "bert",
"position_embedding_type": "absolute",
"output_attentions": false
},
"checkpoint_dtype": "float16"
}
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