Instructions to use tner/bertweet-large-tweetner7-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/bertweet-large-tweetner7-random with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/bertweet-large-tweetner7-random")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/bertweet-large-tweetner7-random") model = AutoModelForTokenClassification.from_pretrained("tner/bertweet-large-tweetner7-random", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87e01531df7c3dfbf14d3bbfbd9a69e1ddcb8cc7d8638b5f24c9cf90fc6f938b
- Size of remote file:
- 1.42 GB
- SHA256:
- d979ed7854716250a7adf5723b97791a45d9976d1da185e2d5c35c127fee4d6d
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