Instructions to use tner/bert-large-tweetner7-2020 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/bert-large-tweetner7-2020 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/bert-large-tweetner7-2020")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/bert-large-tweetner7-2020") model = AutoModelForTokenClassification.from_pretrained("tner/bert-large-tweetner7-2020", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 923679ce8ae5c6d0a55644339f42f62cbdc7cc8aaa36325d461512196e5f8a3a
- Size of remote file:
- 1.33 GB
- SHA256:
- 0174a7ae9725df8b6d0cd040a389986c4f8186ccf04ae1fe2e8986b962581265
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