Instructions to use powervel/bert_multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use powervel/bert_multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="powervel/bert_multi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("powervel/bert_multi") model = AutoModelForSequenceClassification.from_pretrained("powervel/bert_multi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd12a9cd0a2d3dbfd1980b4c2a4a26f179cff4f59e17d39ce814f14691b33ac8
- Size of remote file:
- 5.3 kB
- SHA256:
- b5f7543551f623214aad8923f3f333ac7f8af0a9acbf04a9779884f6fa97bcb2
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