Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use poooj/BertClassificationTest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use poooj/BertClassificationTest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="poooj/BertClassificationTest")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("poooj/BertClassificationTest") model = AutoModelForSequenceClassification.from_pretrained("poooj/BertClassificationTest") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69f95e9d4e2c1dd108e4ca9fd1524cea1239bbc1e07cf4e08757ad1109d10a93
- Size of remote file:
- 438 MB
- SHA256:
- cb66f6e3cc18cfe0895383a7e32057f82f8d03cbdad829a1609bdfe07c0d6d5d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.