Instructions to use miladfa7/model_fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use miladfa7/model_fa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="miladfa7/model_fa")# Load model directly from transformers import AutoTokenizer, TF_AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("miladfa7/model_fa") model = TF_AutoModelForMaskedLM.from_pretrained("miladfa7/model_fa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 442 Bytes
2a03d3e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"architectures": [
"TFBertForMaskedLM"
],
"attention_probs_dropout_prob": 0.1,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"max_position_embeddings": 512,
"model_type": "bert",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"type_vocab_size": 2,
"pad_token_id": 0,
"vocab_size": 100000
} |