Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use LovenOO/BERT_without_preprocessing_grid_search with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LovenOO/BERT_without_preprocessing_grid_search with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LovenOO/BERT_without_preprocessing_grid_search")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LovenOO/BERT_without_preprocessing_grid_search") model = AutoModelForSequenceClassification.from_pretrained("LovenOO/BERT_without_preprocessing_grid_search", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41edf428ea3014662dbc447172931d89ebfc8dc6bb2ad52cde31a7e055e73f76
- Size of remote file:
- 4.03 kB
- SHA256:
- 41c17514e1cbb1f87561f85123546227aba6f12a72e04ddabf52898eb4531e4f
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