Instructions to use softoft/otai-queue-de-bert-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use softoft/otai-queue-de-bert-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="softoft/otai-queue-de-bert-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("softoft/otai-queue-de-bert-v1") model = AutoModelForSequenceClassification.from_pretrained("softoft/otai-queue-de-bert-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d900bec36a36848f99a8b73385204b105fd54eeb3a54e498563d193b01f39104
- Size of remote file:
- 440 MB
- SHA256:
- 267564460f59897d9bb150c184265bc35ed3ae074b0741c3c344f580fa229990
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