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
Download model.safetensors from Andranik/TestPytorchClassification: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Andranik/TestPytorchClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://Andranik/TestPytorchClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Andranik/TestPytorchClassification/resolve/refs%2Fpr%2F1/model.safetensors
268 MB
- Xet hash:
- b2cc40432044b629b2e450aed5eba5c67c2fa881c85c5c7cd48833261628b806
- Size of remote file:
- 268 MB
- SHA256:
- 8b8f7e48b162a4aac5c244c02fbb7a515e079c6380c5ac8e30bd060fef6e6620
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