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:
- 9c93a43315017b4a17599b8a7f1dd56837d2f8fe621bd5c5748e8b8d95656dc3
- Size of remote file:
- 438 MB
- SHA256:
- 5699aa2e7d2c2b8cbcf33cd5103e53bde39332ab65a678924836ef44e495a1cb
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