Instructions to use NPCProgrammer/DBERT_tweet_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NPCProgrammer/DBERT_tweet_tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NPCProgrammer/DBERT_tweet_tuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NPCProgrammer/DBERT_tweet_tuned") model = AutoModelForSequenceClassification.from_pretrained("NPCProgrammer/DBERT_tweet_tuned") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49cd20a2fea6215caff691a6394780c1a6f0df9e4893cd4d3e571d1960e75bb0
- Size of remote file:
- 268 MB
- SHA256:
- e54b02a206caddf48b6800dc8b47ed24842351ef0824f08cc31c60024b5c4074
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