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
| { | |
| "_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 | |
| } | |