Text Classification
Transformers
PyTorch
TensorBoard
English
mobilebert
Generated from Trainer
Eval Results (legacy)
Instructions to use Alireza1044/mobilebert_mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alireza1044/mobilebert_mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Alireza1044/mobilebert_mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Alireza1044/mobilebert_mnli") model = AutoModelForSequenceClassification.from_pretrained("Alireza1044/mobilebert_mnli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7af034f58ccf9a94c4c3d91939ae426f413a8ebd56c70530e3cfd7628853b00
- Size of remote file:
- 3.25 kB
- SHA256:
- 417e0f51cedfa5db038376be7d31d5ff2ab509befdb6ed9d7f0b1948433388b3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.