Instructions to use dvruette/bertweet-large_augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dvruette/bertweet-large_augmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dvruette/bertweet-large_augmented")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dvruette/bertweet-large_augmented") model = AutoModelForSequenceClassification.from_pretrained("dvruette/bertweet-large_augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1d0c680bd069d62bcbe0b89c2f978e0efab41c7a6afad5e9b295db86634beb7
- Size of remote file:
- 1.42 GB
- SHA256:
- c09b973eadc41c1086feb4d6fc3af6dbeafe24e59194d6e3ee6ee6f60c43f49c
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