Instructions to use ashiquejaman/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashiquejaman/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ashiquejaman/output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ashiquejaman/output") model = AutoModelForSequenceClassification.from_pretrained("ashiquejaman/output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 425052afc3a1a214f2084881e996e56e35f5a9f229a42b0fcca2843a789c7ce6
- Size of remote file:
- 4.47 kB
- SHA256:
- 2d39a24c0e6200470333b4e28f7997e61a8a1fa06012fa665f05a7b118ee5e91
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