Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AndrewDOrlov/bert-eval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AndrewDOrlov/bert-eval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AndrewDOrlov/bert-eval")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AndrewDOrlov/bert-eval") model = AutoModelForSequenceClassification.from_pretrained("AndrewDOrlov/bert-eval", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a42a487d5aa4a72880002c279259d3f8bfcf9ac1d60fc7ff26a189c178006e6
- Size of remote file:
- 712 MB
- SHA256:
- 062207dd9d37f8c88894a4011497f733f69949984c9a1258076aa5a2c0a54fe1
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