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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99ac05821bb6e959cf039f89651fca7c26c35081ae8063d3a4c5641241230e1d
- Size of remote file:
- 4.92 kB
- SHA256:
- c38167951c597f5d2a3f5a42e58acd8db9e7cb193ba2e84142688c81aa92d173
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