Text Classification
Transformers
Safetensors
English
roberta
Generated from Trainer
multi_label_classification
text-embeddings-inference
Instructions to use ADS509/BERTweet-large-self-labeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ADS509/BERTweet-large-self-labeling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ADS509/BERTweet-large-self-labeling")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ADS509/BERTweet-large-self-labeling") model = AutoModelForSequenceClassification.from_pretrained("ADS509/BERTweet-large-self-labeling") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67bcae5fefbf6a09bca076a4d19a23373a6bc29c7c645b5868b5c5c4e60ce372
- Size of remote file:
- 5.27 kB
- SHA256:
- 3f03248de6d4f0df254777fc607cccfd915f4a794a519828ee4735e4eaaa7958
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