Instructions to use Andranik/TestPytorchClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Andranik/TestPytorchClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Andranik/TestPytorchClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Andranik/TestPytorchClassification") model = AutoModelForSequenceClassification.from_pretrained("Andranik/TestPytorchClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Delete tokenizer.json
3b6032e -
Delete pytorch_model.bin
469c549 -
Delete config.json
623dbc1 -
Upload tokenizer_config.json
abda47a -
Upload tokenizer.json
13effb7 -
Upload config.json
6124890 -
Upload pytorch_model.bin with git-lfs
896768a -
initial commit
8283a88