Instructions to use junaidali/bert_tokenizer_updated_multilingual_words with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junaidali/bert_tokenizer_updated_multilingual_words with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="junaidali/bert_tokenizer_updated_multilingual_words")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("junaidali/bert_tokenizer_updated_multilingual_words") model = AutoModelForTokenClassification.from_pretrained("junaidali/bert_tokenizer_updated_multilingual_words", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96e6ff1f5974694720e489a9c97562591cf9a167adfb8255d5d7b735e73e3757
- Size of remote file:
- 1.1 GB
- SHA256:
- c057a31777223b5fa2a011525dd99af3e2d652aafaa4c2b02e0cca253b5ece42
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