Instructions to use nxtcoder19/dummy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nxtcoder19/dummy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nxtcoder19/dummy")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nxtcoder19/dummy") model = AutoModelForSequenceClassification.from_pretrained("nxtcoder19/dummy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7024e58ec1619cd90167a748452ef368771fb79ad3ebfa9e4b753ff66230df40
- Size of remote file:
- 438 MB
- SHA256:
- bd61683780ce8f7dca31620b5cd343c717ca9fcd7401d389897fbf831cfb3caf
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