Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use bdanko/bert-tweeteval-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bdanko/bert-tweeteval-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bdanko/bert-tweeteval-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bdanko/bert-tweeteval-distilbert") model = AutoModelForSequenceClassification.from_pretrained("bdanko/bert-tweeteval-distilbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36763569528b24871446af4af3a8b2fcb8f5336a50d51f5471762f29138faf51
- Size of remote file:
- 5.27 kB
- SHA256:
- 4994f935f013b95f32c1aa1bc623485f52273e51c21799cffdbeba97310aecb1
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