Instructions to use sundea/text1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sundea/text1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sundea/text1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sundea/text1") model = AutoModelForSequenceClassification.from_pretrained("sundea/text1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3036748a182465c6c73e76a19ab8fccbaee1b58c793678da6611059834371e2
- Size of remote file:
- 409 MB
- SHA256:
- 3be25d1120a92ddf094a9badee6871d398f1459516460ff306bf0f3c9c97e999
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