Token Classification
Transformers
Safetensors
Finnish
electra
punctuation-restoration
sentence-boundary-detection
truecasing
speech-recognition
streaming
finnish
Instructions to use samuli/mateli-punct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use samuli/mateli-punct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="samuli/mateli-punct")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("samuli/mateli-punct") model = AutoModelForTokenClassification.from_pretrained("samuli/mateli-punct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,602 Bytes
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"add_cross_attention": false,
"architectures": [
"ElectraForTokenClassification"
],
"attention_probs_dropout_prob": 0.1,
"bos_token_id": null,
"classifier_dropout": null,
"dtype": "float32",
"embedding_size": 768,
"eos_token_id": null,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 256,
"id2label": {
"0": "O",
"1": "O|U",
"2": "O|A",
"3": ",",
"4": ",|U",
"5": ",|A",
"6": ".",
"7": ".|U",
"8": ".|A",
"9": "?",
"10": "?|U",
"11": "?|A",
"12": "!",
"13": "!|U",
"14": "!|A"
},
"initializer_range": 0.02,
"intermediate_size": 1024,
"is_decoder": false,
"label2id": {
"!": 12,
"!|A": 14,
"!|U": 13,
",": 3,
",|A": 5,
",|U": 4,
".": 6,
".|A": 8,
".|U": 7,
"?": 9,
"?|A": 11,
"?|U": 10,
"O": 0,
"O|A": 2,
"O|U": 1
},
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "electra",
"num_attention_heads": 4,
"num_hidden_layers": 12,
"pad_token_id": 0,
"pause_markers": {
"buckets": [
"[unused1]",
"[unused2]",
"[unused3]",
"[unused4]",
"[unused5]"
],
"edges": [
0.14,
0.3,
0.5,
0.78,
1.18
],
"flag": "[unused0]"
},
"position_embedding_type": "absolute",
"summary_activation": "gelu",
"summary_last_dropout": 0.1,
"summary_type": "first",
"summary_use_proj": true,
"tie_word_embeddings": true,
"transformers_version": "5.19.0",
"type_vocab_size": 2,
"use_cache": true,
"vocab_size": 26020
} |