Feature Extraction
Transformers
Safetensors
qwen3_5
image-text-to-text
multimodal-embedding
retrieval
evaluation
custom_code
Instructions to use woooooz/WeMM-Embedding-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use woooooz/WeMM-Embedding-9B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="woooooz/WeMM-Embedding-9B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("woooooz/WeMM-Embedding-9B", trust_remote_code=True) model = AutoModelForMultimodalLM.from_pretrained("woooooz/WeMM-Embedding-9B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- 9.93 kB
- 40.9 kB
- 3.01 kB
- 4.89 kB
- 14.8 kB
- 14.5 kB
- 33.5 kB
- 3.33 kB
- 4.85 kB
- 49.2 kB
- 14.3 kB
- 38.6 kB
- 3.23 kB
- 7.08 kB
- 14.6 kB
- 2.83 kB
- 5.81 kB
- 3.02 kB
- 32 kB
- 30.6 kB
- 5.08 kB
- 19 kB
- 118 kB
- 2.01 kB
- 10.5 kB
- 4.71 kB
- 24.5 kB
- 28.3 kB
- 4.35 kB
- 4.41 kB
- 53.2 kB
- 4.88 kB
- 1.17 kB
- 4.85 kB
- 2.42 kB
- 5.58 kB
- 3.31 kB
- 64.9 kB
- 1.99 kB
- 10.5 kB
- 9.74 kB
- 3.62 kB