Instructions to use Noobbbbb/banglabert-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Noobbbbb/banglabert-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Noobbbbb/banglabert-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Noobbbbb/banglabert-ner") model = AutoModelForTokenClassification.from_pretrained("Noobbbbb/banglabert-ner") - Notebooks
- Google Colab
- Kaggle
File size: 1,620 Bytes
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"add_cross_attention": false,
"architectures": [
"ElectraForTokenClassification"
],
"attention_probs_dropout_prob": 0.1,
"bos_token_id": null,
"classifier_dropout": null,
"dtype": "float32",
"embedding_size": 768,
"eos_token_id": null,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"id2label": {
"0": "B-D&T",
"1": "B-EVENT",
"2": "B-GPE",
"3": "B-LOC",
"4": "B-MISC",
"5": "B-NUM",
"6": "B-ORG",
"7": "B-PER",
"8": "B-T&T",
"9": "B-UNIT",
"10": "I-D&T",
"11": "I-EVENT",
"12": "I-GPE",
"13": "I-LOC",
"14": "I-MISC",
"15": "I-NUM",
"16": "I-ORG",
"17": "I-PER",
"18": "I-T&T",
"19": "I-UNIT",
"20": "O"
},
"initializer_range": 0.02,
"intermediate_size": 3072,
"is_decoder": false,
"label2id": {
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"B-GPE": 2,
"B-LOC": 3,
"B-MISC": 4,
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"I-PER": 17,
"I-T&T": 18,
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"O": 20
},
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "electra",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 0,
"summary_activation": "gelu",
"summary_last_dropout": 0.1,
"summary_type": "first",
"summary_use_proj": true,
"tie_word_embeddings": true,
"transformers_version": "5.0.0",
"type_vocab_size": 2,
"use_cache": false,
"vocab_size": 32000
}
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