Fill-Mask
Transformers
Safetensors
Piemontese
gemma3_text
feature-extraction
trimmed
text-generation-inference
Instructions to use alphaedge-ai/embeddinggemma-pms-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphaedge-ai/embeddinggemma-pms-16384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alphaedge-ai/embeddinggemma-pms-16384")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("alphaedge-ai/embeddinggemma-pms-16384") model = AutoModel.from_pretrained("alphaedge-ai/embeddinggemma-pms-16384") - Notebooks
- Google Colab
- Kaggle
| { | |
| "word_embedding_dimension": 768, | |
| "pooling_mode_cls_token": false, | |
| "pooling_mode_mean_tokens": true, | |
| "pooling_mode_max_tokens": false, | |
| "pooling_mode_mean_sqrt_len_tokens": false, | |
| "pooling_mode_weightedmean_tokens": false, | |
| "pooling_mode_lasttoken": false, | |
| "include_prompt": true | |
| } |