Instructions to use onnx-community/mmBERT-small-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use onnx-community/mmBERT-small-ONNX with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('fill-mask', 'onnx-community/mmBERT-small-ONNX');
File size: 1,332 Bytes
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"_attn_implementation_autoset": true,
"_name_or_path": "jhu-clsp/mmBERT-small",
"architectures": [
"ModernBertForMaskedLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 2,
"classifier_activation": "gelu",
"classifier_bias": false,
"classifier_dropout": 0.0,
"classifier_pooling": "mean",
"cls_token_id": 1,
"decoder_bias": true,
"deterministic_flash_attn": false,
"embedding_dropout": 0.0,
"eos_token_id": 1,
"global_attn_every_n_layers": 3,
"global_rope_theta": 160000,
"gradient_checkpointing": false,
"hidden_activation": "gelu",
"hidden_size": 384,
"initializer_cutoff_factor": 2.0,
"initializer_range": 0.02,
"intermediate_size": 1152,
"layer_norm_eps": 1e-05,
"local_attention": 128,
"local_rope_theta": 160000,
"mask_token_id": 4,
"max_position_embeddings": 8192,
"mlp_bias": false,
"mlp_dropout": 0.0,
"model_type": "modernbert",
"norm_bias": false,
"norm_eps": 1e-05,
"num_attention_heads": 6,
"num_hidden_layers": 22,
"pad_token_id": 0,
"position_embedding_type": "sans_pos",
"reference_compile": null,
"repad_logits_with_grad": false,
"sep_token_id": 1,
"sparse_pred_ignore_index": -100,
"sparse_prediction": false,
"torch_dtype": "float32",
"transformers_version": "4.49.0",
"vocab_size": 256000
}
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