Instructions to use emi08/maske with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emi08/maske with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="emi08/maske")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("emi08/maske") model = AutoModelForTokenClassification.from_pretrained("emi08/maske", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from emi08/maske: direct link, hf CLI and curl.
- Browser
- Download file 2.7 kB
-
https://huggingface.co/emi08/maske/resolve/main/config.json
- Command line
-
hf download hf://emi08/maske/config.json
-
curl -L -o config.json https://huggingface.co/emi08/maske/resolve/main/config.json
2.7 kB
| { | |
| "architectures": [ | |
| "ModernBertForTokenClassification" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 50281, | |
| "classifier_activation": "silu", | |
| "classifier_bias": false, | |
| "classifier_dropout": 0.0, | |
| "classifier_pooling": "mean", | |
| "cls_token_id": 2, | |
| "decoder_bias": true, | |
| "deterministic_flash_attn": false, | |
| "dtype": "float32", | |
| "embedding_dropout": 0.0, | |
| "eos_token_id": 50000, | |
| "global_attn_every_n_layers": 3, | |
| "gradient_checkpointing": false, | |
| "hidden_activation": "gelu", | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "O", | |
| "1": "B-PER", | |
| "2": "I-PER", | |
| "3": "B-ORG", | |
| "4": "I-ORG", | |
| "5": "B-LOC", | |
| "6": "I-LOC", | |
| "7": "B-TC_NO", | |
| "8": "I-TC_NO", | |
| "9": "B-IBAN", | |
| "10": "I-IBAN", | |
| "11": "B-PHONE", | |
| "12": "I-PHONE", | |
| "13": "B-PLATE", | |
| "14": "I-PLATE", | |
| "15": "B-EMAIL", | |
| "16": "I-EMAIL", | |
| "17": "B-ADDR", | |
| "18": "I-ADDR" | |
| }, | |
| "initializer_cutoff_factor": 2.0, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1152, | |
| "label2id": { | |
| "O": "0", | |
| "B-PER": "1", | |
| "I-PER": "2", | |
| "B-ORG": "3", | |
| "I-ORG": "4", | |
| "B-LOC": "5", | |
| "I-LOC": "6", | |
| "B-TC_NO": "7", | |
| "I-TC_NO": "8", | |
| "B-IBAN": "9", | |
| "I-IBAN": "10", | |
| "B-PHONE": "11", | |
| "I-PHONE": "12", | |
| "B-PLATE": "13", | |
| "I-PLATE": "14", | |
| "B-EMAIL": "15", | |
| "I-EMAIL": "16", | |
| "B-ADDR": "17", | |
| "I-ADDR": "18" | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "layer_types": [ | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention" | |
| ], | |
| "local_attention": 128, | |
| "max_position_embeddings": 8192, | |
| "mlp_bias": false, | |
| "mlp_dropout": 0.0, | |
| "model_type": "modernbert", | |
| "norm_bias": false, | |
| "norm_eps": 1e-05, | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 22, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "rope_parameters": { | |
| "full_attention": { | |
| "rope_theta": 10000.0, | |
| "rope_type": "default" | |
| }, | |
| "sliding_attention": { | |
| "rope_theta": 10000.0, | |
| "rope_type": "default" | |
| } | |
| }, | |
| "sep_token_id": 3, | |
| "sparse_pred_ignore_index": -100, | |
| "sparse_prediction": false, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.20.2", | |
| "use_cache": false, | |
| "vocab_size": 50008 | |
| } |