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
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9e53dd0c4d0e674bb7380b332a7d74dafe915cbc57f7227b1f61fb4fd399291e
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size 437977104
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