Instructions to use codern/downstream-german-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codern/downstream-german-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="codern/downstream-german-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("codern/downstream-german-bert") model = AutoModelForTokenClassification.from_pretrained("codern/downstream-german-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 2,505 Bytes
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],
"attention_probs_dropout_prob": 0.1,
"classifier_dropout": null,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"id2label": {
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"UK-Schuhgr\u00f6\u00dfe": 25,
"US-Schuhgr\u00f6\u00dfe": 6,
"Verschluss": 18,
"Zwischensohlen-Typ": 14
},
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "bert",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 0,
"position_embedding_type": "absolute",
"torch_dtype": "float32",
"transformers_version": "4.33.0",
"type_vocab_size": 2,
"use_cache": true,
"vocab_size": 31102
}
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