Feature Extraction
Transformers
Safetensors
qwen3_5
multimodal embedding
qwen
embedding
distillation
vl
vision-language
vl-embedding
image-text-to-text
sentence-similarity
custom_code
Eval Results (legacy)
Instructions to use radi-cho/cho-embedding-0.8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radi-cho/cho-embedding-0.8b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="radi-cho/cho-embedding-0.8b", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("radi-cho/cho-embedding-0.8b", trust_remote_code=True) model = AutoModel.from_pretrained("radi-cho/cho-embedding-0.8b", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
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