Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use alejoa/bert-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alejoa/bert-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alejoa/bert-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alejoa/bert-sst2") model = AutoModelForSequenceClassification.from_pretrained("alejoa/bert-sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a97298cd617c06768da410769b181e27069c5ed194d362f26d5aeb97be20ff5d
- Size of remote file:
- 438 MB
- SHA256:
- 1fd372748cc40dbd1bdd543295a8cbc46c1d1a42c2debee580b3d01ec565dfd8
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