Text Classification
Transformers
Safetensors
distilbert
intent-detection
callcenter
customer-support
fine-tuned
text-embeddings-inference
Instructions to use karimenBR/callcenter-transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karimenBR/callcenter-transformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karimenBR/callcenter-transformer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karimenBR/callcenter-transformer") model = AutoModelForSequenceClassification.from_pretrained("karimenBR/callcenter-transformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from karimenBR/callcenter-transformer: direct link, hf CLI and curl.
- Browser
- Download file 1.1 kB
-
https://huggingface.co/karimenBR/callcenter-transformer/resolve/main/config.json
- Command line
-
hf download hf://karimenBR/callcenter-transformer/config.json
-
curl -L -o config.json https://huggingface.co/karimenBR/callcenter-transformer/resolve/main/config.json
1.1 kB
| { | |
| "_name_or_path": "./models/transformer/final_model", | |
| "activation": "gelu", | |
| "architectures": [ | |
| "DistilBertForSequenceClassification" | |
| ], | |
| "attention_dropout": 0.1, | |
| "dim": 768, | |
| "dropout": 0.1, | |
| "hidden_dim": 3072, | |
| "id2label": { | |
| "0": "Access", | |
| "1": "Administrative rights", | |
| "2": "HR Support", | |
| "3": "Hardware", | |
| "4": "Internal Project", | |
| "5": "Miscellaneous", | |
| "6": "Purchase", | |
| "7": "Storage" | |
| }, | |
| "initializer_range": 0.02, | |
| "label2id": { | |
| "Access": 0, | |
| "Administrative rights": 1, | |
| "HR Support": 2, | |
| "Hardware": 3, | |
| "Internal Project": 4, | |
| "Miscellaneous": 5, | |
| "Purchase": 6, | |
| "Storage": 7 | |
| }, | |
| "max_position_embeddings": 512, | |
| "model_type": "distilbert", | |
| "n_heads": 12, | |
| "n_layers": 6, | |
| "output_past": true, | |
| "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, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.44.2", | |
| "vocab_size": 119547 | |
| } | |