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:
- 9e4afc9cc4bfa7689fadb00130dc6601833aef294693246049b42d982986b9e8
- Size of remote file:
- 4.16 kB
- SHA256:
- 562aad4794f979667624a2a43c20d2b907ceecfe377614aaffade22539112692
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