Instructions to use tiny-random/embeddinggemma-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiny-random/embeddinggemma-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="tiny-random/embeddinggemma-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("tiny-random/embeddinggemma-2") model = AutoModel.from_pretrained("tiny-random/embeddinggemma-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 411 Bytes
76de4e3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"source_model": {
"name": "google/embeddinggemma-2",
"commit_id": "914f7f89142e33e77833254d9c9b90c3cef7303b"
},
"env": {
"python": "3.12.13",
"packages": {
"Pillow": "13.0.0",
"huggingface_hub": "2.3.0",
"numpy": "2.3.5",
"safetensors": "0.8.0",
"tokenizers": "0.23.3",
"torch": "2.13.0",
"transformers": "5.19.0"
},
"cuda": "13.0"
}
} |