Instructions to use Syldehayem/bert_tiny_embedder_train_best with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Syldehayem/bert_tiny_embedder_train_best with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Syldehayem/bert_tiny_embedder_train_best")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Syldehayem/bert_tiny_embedder_train_best") model = AutoModel.from_pretrained("Syldehayem/bert_tiny_embedder_train_best", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76eb9f1cb89f33fffa6addf0da758704e684cba45d446e0a659473c736f245b7
- Size of remote file:
- 17.5 MB
- SHA256:
- 2ad735a1784229d20f15fca846b3d87fad883cecd21965db7bd5f6687ee4d67a
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