Image Feature Extraction
Transformers
Safetensors
dreamsim
feature-extraction
perceptual-similarity
custom_code
Instructions to use bigshanedogg/dreamsim-ensemble with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bigshanedogg/dreamsim-ensemble with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="bigshanedogg/dreamsim-ensemble", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bigshanedogg/dreamsim-ensemble", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 488 Bytes
f918a65 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"architectures": [
"DreamSimModel"
],
"model_type": "dreamsim",
"auto_map": {
"AutoConfig": "configuration_dreamsim.DreamSimConfig",
"AutoModel": "modeling_dreamsim.DreamSimModel"
},
"dreamsim_type": "ensemble",
"model_types": "dino_vitb16,clip_vitb16,open_clip_vitb16",
"feat_types": "cls,embedding,embedding",
"strides": "16,16,16",
"img_size": 224,
"embed_size": 1792,
"normalize_embeds": true,
"lora_merged": true,
"torch_dtype": "float32"
}
|