Instructions to use marcchew/testv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcchew/testv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcchew/testv2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcchew/testv2") model = AutoModelForSequenceClassification.from_pretrained("marcchew/testv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b73569da04b914c081dfaf1a9b7309831b3535b19021e453dca5123163f5b07
- Size of remote file:
- 5.18 kB
- SHA256:
- 82819ab5774e79d17636f9b9f3326d396ce7e52efbd5a37cbb2aa48826f6bc8a
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