Instructions to use AXERA-TECH/jina-embeddings-v5-omni-nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AXERA-TECH/jina-embeddings-v5-omni-nano with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AXERA-TECH/jina-embeddings-v5-omni-nano")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AXERA-TECH/jina-embeddings-v5-omni-nano", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "device": "AX650 / NPU3", | |
| "warmup": 3, | |
| "repeat": 20, | |
| "command": "ax_run_model --model=<package-local-axmodel> --warmup=3 --repeat=20", | |
| "text": { | |
| "shape_group": 1, | |
| "layer_average_ms": [ | |
| 2.357, | |
| 2.391, | |
| 2.345, | |
| 2.340, | |
| 2.345, | |
| 2.346, | |
| 2.345, | |
| 2.342, | |
| 2.342, | |
| 2.343, | |
| 2.341, | |
| 2.340 | |
| ], | |
| "layer_average_sum_ms": 28.177, | |
| "post_average_ms": 5.601 | |
| }, | |
| "vision": { | |
| "tower_average_ms": 15.838, | |
| "merger_average_ms": { | |
| "retrieval": 0.671, | |
| "clustering": 0.671 | |
| } | |
| }, | |
| "audio": { | |
| "tower_average_ms": 211.082, | |
| "projector_average_ms": { | |
| "retrieval": 0.239, | |
| "clustering": 0.242 | |
| } | |
| } | |
| } | |