Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use bdanko/bert-tweeteval-distilroberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bdanko/bert-tweeteval-distilroberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bdanko/bert-tweeteval-distilroberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bdanko/bert-tweeteval-distilroberta") model = AutoModelForSequenceClassification.from_pretrained("bdanko/bert-tweeteval-distilroberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e42062304d049ffdc1d6fbdf1800b9fce85d22911ef9df234a064c146ef3ef44
- Size of remote file:
- 5.27 kB
- SHA256:
- 94c5e3f9fdd38fc45e2f7a812a1437b5b8b2e327b309d1189f5a03437f5ccbc6
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