Transformers
PyTorch
TensorFlow
JAX
English
bert
pretraining
singapore
sg
singlish
malaysia
ms
manglish
bert-base-uncased
Instructions to use zanelim/singbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zanelim/singbert with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("zanelim/singbert") model = AutoModelForPreTraining.from_pretrained("zanelim/singbert") - Notebooks
- Google Colab
- Kaggle
File size: 471 Bytes
6d20712 08ad285 6d20712 08ad285 6d20712 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"architectures": [
"BertForPreTraining"
],
"attention_probs_dropout_prob": 0.1,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "bert",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 0,
"type_vocab_size": 2,
"vocab_size": 30522
}
|