Token Classification
Transformers
Safetensors
Bengali
electra
bengali
bangla
punctuation-restoration
asr-post-processing
banglaprcorpus
Instructions to use HasinManjare/bangla-punctuation-extended-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HasinManjare/bangla-punctuation-extended-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HasinManjare/bangla-punctuation-extended-v3")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HasinManjare/bangla-punctuation-extended-v3") model = AutoModelForTokenClassification.from_pretrained("HasinManjare/bangla-punctuation-extended-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,073 Bytes
8ca776b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | {
"architectures": [
"ElectraForTokenClassification"
],
"attention_probs_dropout_prob": 0.1,
"classifier_dropout": null,
"dtype": "float32",
"embedding_size": 768,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"id2label": {
"0": "O",
"1": ",",
"2": "\u0964",
"3": "?",
"4": "!",
"5": ";",
"6": ":",
"7": "\u2026",
"8": "-",
"9": "\u0983"
},
"initializer_range": 0.02,
"intermediate_size": 3072,
"label2id": {
"!": 4,
",": 1,
"-": 8,
":": 6,
";": 5,
"?": 3,
"O": 0,
"\u0964": 2,
"\u0983": 9,
"\u2026": 7
},
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "electra",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 0,
"position_embedding_type": "absolute",
"summary_activation": "gelu",
"summary_last_dropout": 0.1,
"summary_type": "first",
"summary_use_proj": true,
"transformers_version": "4.57.6",
"type_vocab_size": 2,
"use_cache": true,
"vocab_size": 32000
}
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