Instructions to use Rostlab/prot_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rostlab/prot_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Rostlab/prot_bert")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Rostlab/prot_bert", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 361 Bytes
0151113 460102a 0151113 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"architectures": [
"BertForMaskedLM"
],
"attention_probs_dropout_prob": 0.0,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.0,
"hidden_size": 1024,
"initializer_range": 0.02,
"intermediate_size": 4096,
"max_position_embeddings": 40000,
"num_attention_heads": 16,
"num_hidden_layers": 30,
"type_vocab_size": 2,
"vocab_size": 30
}
|