Text Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use thusken/nb-bert-base-ctr-regression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thusken/nb-bert-base-ctr-regression with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thusken/nb-bert-base-ctr-regression")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thusken/nb-bert-base-ctr-regression") model = AutoModelForSequenceClassification.from_pretrained("thusken/nb-bert-base-ctr-regression") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e15157df54695a48c891c2f88a598fdc830bfb75ada8fbbfad380ffd8b5c09bd
- Size of remote file:
- 712 MB
- SHA256:
- b98892882008ee513d4ccb5ba42dba3f33f5803bcef6f8e740d25bdddffb94fe
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