Instructions to use ssun32/bert_base_nli_turkle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ssun32/bert_base_nli_turkle with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ssun32/bert_base_nli_turkle")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ssun32/bert_base_nli_turkle") model = AutoModel.from_pretrained("ssun32/bert_base_nli_turkle", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89a9b15cb05bad78e3e4c80097f50e494e186b7ff3db4b8c721e813fca557c6e
- Size of remote file:
- 438 MB
- SHA256:
- e0a4f5334f9cf1a2abfa526b9f31f08b163eeab924a8ba9fb9c026221dcc4cab
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