Instructions to use tner/bert-large-tweetner7-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/bert-large-tweetner7-random with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/bert-large-tweetner7-random")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/bert-large-tweetner7-random") model = AutoModelForTokenClassification.from_pretrained("tner/bert-large-tweetner7-random") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5617522d3b708a47e8c0157627753708aac5f8bb6db52c34b7e67742de547cd
- Size of remote file:
- 1.33 GB
- SHA256:
- cff05905c403351f1ae33ed920d359cfa954961d6c897a5a273c0302cb29e01e
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