Instructions to use ahmedabdelali/bert-base-qarib with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmedabdelali/bert-base-qarib with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ahmedabdelali/bert-base-qarib")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ahmedabdelali/bert-base-qarib") model = AutoModelForMaskedLM.from_pretrained("ahmedabdelali/bert-base-qarib", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 576 Bytes
5e757e5 a29b190 357c3d1 a29b190 5e757e5 ef485b3 5e757e5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"architectures": [
"BertForMaskedLM"
],
"attention_probs_dropout_prob": 0.1,
"directionality": "bidi",
"hidden_act": "gelu",
"model_type": "bert",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"max_position_embeddings": 512,
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pooler_fc_size": 768,
"pooler_num_attention_heads": 12,
"pooler_num_fc_layers": 3,
"pooler_size_per_head": 128,
"pooler_type": "first_token_transform",
"type_vocab_size": 2,
"vocab_size": 64000
}
|