Instructions to use mohammadmahdinouri/final_modernalbert_checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohammadmahdinouri/final_modernalbert_checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mohammadmahdinouri/final_modernalbert_checkpoints")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("mohammadmahdinouri/final_modernalbert_checkpoints", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 670 Bytes
a64ea0e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | {
"adapter_reduction": 16,
"architectures": [
"ModernALBERTForMaskedLM"
],
"attention_probs_dropout_prob": 0.1,
"classifier_dropout": null,
"embedding_size": 128,
"group_depth": 8,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 1024,
"initializer_range": 0.02,
"intermediate_size": 8192,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 8192,
"model_type": "ModernALBERT",
"num_attention_heads": 16,
"num_hidden_layers": 24,
"output_hidden_states": true,
"pad_token_id": 0,
"torch_dtype": "bfloat16",
"transformers_version": "4.54.1",
"use_adapter": true,
"use_cache": true,
"vocab_size": 50368
}
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