Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use jayavibhav/bert-classification-5ksamples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayavibhav/bert-classification-5ksamples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jayavibhav/bert-classification-5ksamples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jayavibhav/bert-classification-5ksamples") model = AutoModelForSequenceClassification.from_pretrained("jayavibhav/bert-classification-5ksamples") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
26a8ae3 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:6af337fcb0877f3e9d093096079df3d4a679bef6d92e07355a2c20f6b8331551
size 3963
|