Token Classification
Transformers
Safetensors
xmod
code-switching
language-identification
child-speech
multilingual
Instructions to use ZurichNLP/SwissBERT-CS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZurichNLP/SwissBERT-CS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ZurichNLP/SwissBERT-CS")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ZurichNLP/SwissBERT-CS") model = AutoModelForTokenClassification.from_pretrained("ZurichNLP/SwissBERT-CS") - Notebooks
- Google Colab
- Kaggle
File size: 1,179 Bytes
45ff303 | 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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | {
"_name_or_path": "ZurichNLP/swissbert",
"adapter_layer_norm": false,
"adapter_reduction_factor": 2,
"adapter_reuse_layer_norm": true,
"architectures": [
"XmodForTokenClassification"
],
"attention_probs_dropout_prob": 0.1,
"bos_token_id": 0,
"classifier_dropout": null,
"default_language": "gsw",
"eos_token_id": 2,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"id2label": {
"0": "english",
"1": "french",
"2": "italian",
"3": "other",
"4": "swissgerman"
},
"initializer_range": 0.02,
"intermediate_size": 3072,
"label2id": {
"english": 0,
"french": 1,
"italian": 2,
"other": 3,
"swissgerman": 4
},
"languages": [
"de_CH",
"fr_CH",
"it_CH",
"rm_CH",
"gsw"
],
"layer_norm_eps": 1e-05,
"ln_before_adapter": true,
"max_position_embeddings": 514,
"model_type": "xmod",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 1,
"position_embedding_type": "absolute",
"pre_norm": false,
"torch_dtype": "float32",
"transformers_version": "4.35.2",
"type_vocab_size": 1,
"use_cache": true,
"vocab_size": 50262
}
|