Instructions to use jpancorbTaniwa/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jpancorbTaniwa/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jpancorbTaniwa/test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jpancorbTaniwa/test") model = AutoModelForSequenceClassification.from_pretrained("jpancorbTaniwa/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9873c88960abff6af54a402238d79a8cf6ea28c8c81e366728d0b74340142d18
- Size of remote file:
- 439 MB
- SHA256:
- 96012e374a4933f814b6999eb4109e3860b0c24371965afcb28590fcfba77b08
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