Instructions to use tner/bert-large-tweetner7-continuous with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/bert-large-tweetner7-continuous with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/bert-large-tweetner7-continuous")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/bert-large-tweetner7-continuous") model = AutoModelForTokenClassification.from_pretrained("tner/bert-large-tweetner7-continuous", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aef76074ad0afd9863be0479ecaebcd16302a3f7626778aae897e59063c3c84e
- Size of remote file:
- 1.33 GB
- SHA256:
- c617a3c0085e00e68393786f9ceeb4bd62088311a8a09e68e39c37430180f22a
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