Instructions to use vantaa32/models-moved with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vantaa32/models-moved with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vantaa32/models-moved")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vantaa32/models-moved") model = AutoModelForSequenceClassification.from_pretrained("vantaa32/models-moved", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51f462977b80364c9c248bcc52087c609590f2748f93efe320fb9e7198ae79d0
- Size of remote file:
- 4.92 kB
- SHA256:
- 2cda1539e5bee0cdc58c60475ba700406ef38c99fef70b8c359748aa8338e671
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