Instructions to use Syldehayem/bert_tiny_embedder_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Syldehayem/bert_tiny_embedder_train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Syldehayem/bert_tiny_embedder_train")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Syldehayem/bert_tiny_embedder_train") model = AutoModel.from_pretrained("Syldehayem/bert_tiny_embedder_train") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fca6b3d154cca83f93000de241620b4e23fd2df52774ae37c00eb0687c4fbf18
- Size of remote file:
- 17.5 MB
- SHA256:
- b31070c0599edcdb5e95d61d269da06e0773e9f934faee69546be8ac86e484c5
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