Instructions to use argv947059/example-based-ner-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use argv947059/example-based-ner-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="argv947059/example-based-ner-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("argv947059/example-based-ner-bert") model = AutoModel.from_pretrained("argv947059/example-based-ner-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
AXG143 commited on
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Browse files- example_based_bert_tokenizer/added_tokens.json β added_tokens.json +0 -0
- example_based_ner_bert/config.json β config.json +0 -0
- example_based_ner_bert/pytorch_model.bin β pytorch_model.bin +0 -0
- example_based_bert_tokenizer/special_tokens_map.json β special_tokens_map.json +0 -0
- example_based_bert_tokenizer/tokenizer_config.json β tokenizer_config.json +0 -0
- example_based_bert_tokenizer/vocab.txt β vocab.txt +0 -0
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