Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use bradmin/reward-bert-duplicate-answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bradmin/reward-bert-duplicate-answer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bradmin/reward-bert-duplicate-answer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bradmin/reward-bert-duplicate-answer") model = AutoModelForSequenceClassification.from_pretrained("bradmin/reward-bert-duplicate-answer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b69fc37baf120a47e61eacb4b178b137d9799587eac072ef46b74a6c1862448d
- Size of remote file:
- 2.69 GB
- SHA256:
- 647f7247b4c4ff44fbc088db4560b6e09dff6a774e37fd143e4d2ddcb6668c92
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.