Instructions to use tner/bert-base-tweetner7-all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/bert-base-tweetner7-all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/bert-base-tweetner7-all")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/bert-base-tweetner7-all") model = AutoModelForTokenClassification.from_pretrained("tner/bert-base-tweetner7-all") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 730dd061aac2ad4f910100dfdab7cb69ad7dc2987db0ca98257143b6244103a1
- Size of remote file:
- 431 MB
- SHA256:
- b142b70f0682eb7d488f412faaaf8342a1719c4ea74bfe17cc225f10ab189035
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