Text Classification
Transformers
Safetensors
Indonesian
bert
indobert
intent-classification
text-embeddings-inference
Instructions to use Firdania/sindesa-indobert-intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Firdania/sindesa-indobert-intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Firdania/sindesa-indobert-intent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Firdania/sindesa-indobert-intent") model = AutoModelForSequenceClassification.from_pretrained("Firdania/sindesa-indobert-intent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_num_labels": 5, | |
| "architectures": [ | |
| "BertForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "directionality": "bidi", | |
| "dtype": "float32", | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "oos", | |
| "1": "tanya_durasi", | |
| "2": "tanya_informasi", | |
| "3": "tanya_jadwal", | |
| "4": "tanya_kendala", | |
| "5": "tanya_lokasi", | |
| "6": "tanya_pembaruan", | |
| "7": "tanya_pembayaran", | |
| "8": "tanya_prosedur", | |
| "9": "tanya_status", | |
| "10": "tanya_syarat" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "oos": 0, | |
| "tanya_durasi": 1, | |
| "tanya_informasi": 2, | |
| "tanya_jadwal": 3, | |
| "tanya_kendala": 4, | |
| "tanya_lokasi": 5, | |
| "tanya_pembaruan": 6, | |
| "tanya_pembayaran": 7, | |
| "tanya_prosedur": 8, | |
| "tanya_status": 9, | |
| "tanya_syarat": 10 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "pooler_fc_size": 768, | |
| "pooler_num_attention_heads": 12, | |
| "pooler_num_fc_layers": 3, | |
| "pooler_size_per_head": 128, | |
| "pooler_type": "first_token_transform", | |
| "position_embedding_type": "absolute", | |
| "transformers_version": "4.57.6", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 50000 | |
| } | |