Instructions to use Oranblock/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Oranblock/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Oranblock/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Oranblock/results") model = AutoModelForSequenceClassification.from_pretrained("Oranblock/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9011a3072f653b2eb2c9e25ee2e64ec8b5dd5950536f9f92e4c08c4c5c8aad5f
- Size of remote file:
- 5.11 kB
- SHA256:
- 4958956d145c13c02a74bf5fd162a90f980e051e51c7976d7b34a1222ff3b7f1
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