Instructions to use junaidali/updated_multilinngual_bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junaidali/updated_multilinngual_bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="junaidali/updated_multilinngual_bert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("junaidali/updated_multilinngual_bert_model") model = AutoModelForTokenClassification.from_pretrained("junaidali/updated_multilinngual_bert_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7f6660f2789114f143f99cce59e469e8ed9383ac5e7b6ffd31c05b98f842266
- Size of remote file:
- 1.1 GB
- SHA256:
- 3a5624dc5627cf2d7d7f3e186637af80e2e40fef808c0c915e04f87056e730da
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