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:
- ca9574186489181302b7270ec33e00e78a5f9e88b709bd3456c7683e1e21a7c6
- Size of remote file:
- 433 MB
- SHA256:
- e7a48e2c758b8bcfe7886a967b557a981b3facb33cbef4697cfaf5bb890822f8
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