Feature Extraction
Transformers
Safetensors
OpenVINO
PyTorch
English
biomedical
bert
embeddings
benchmark
sentence-similarity
intel-xeon
cpu-inference
quantization
event-separation
clinical-nlp
Instructions to use Dotsin/lbm-benchmarking-embeddingsFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dotsin/lbm-benchmarking-embeddingsFT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Dotsin/lbm-benchmarking-embeddingsFT")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Dotsin/lbm-benchmarking-embeddingsFT", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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