Instructions to use Tensorride/Classifier_MPI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tensorride/Classifier_MPI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tensorride/Classifier_MPI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tensorride/Classifier_MPI") model = AutoModelForSequenceClassification.from_pretrained("Tensorride/Classifier_MPI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 865e7b4cfaa4885ff7fd9b660e48e82679c77589732eee16344f8048479a7770
- Size of remote file:
- 268 MB
- SHA256:
- 20e1416d5215403bb75e16290a7976ac44cf27331640a11ebfc6a77589288ce2
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