Instructions to use Capreolus/birch-bert-large-mb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Capreolus/birch-bert-large-mb with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForNextSentencePrediction tokenizer = AutoTokenizer.from_pretrained("Capreolus/birch-bert-large-mb") model = AutoModelForNextSentencePrediction.from_pretrained("Capreolus/birch-bert-large-mb") - Notebooks
- Google Colab
- Kaggle
File size: 483 Bytes
570f0a1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"architectures": [
"BertForNextSentencePrediction"
],
"attention_probs_dropout_prob": 0.1,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 1024,
"initializer_range": 0.02,
"intermediate_size": 4096,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "bert",
"num_attention_heads": 16,
"num_hidden_layers": 24,
"pad_token_id": 0,
"type_vocab_size": 2,
"vocab_size": 30522
}
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