Feature Extraction
Transformers
Safetensors
English
fuse_matcher
image-text-matching
flickr8k
cnn
vision-language
custom_code
Eval Results (legacy)
Instructions to use harpertoken/fuse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harpertoken/fuse with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="harpertoken/fuse", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("harpertoken/fuse", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 368 Bytes
13f63ac | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"architectures": [
"FuseMatcher"
],
"auto_map": {
"AutoConfig": "modeling_fuse.FuseConfig",
"AutoModel": "modeling_fuse.FuseMatcher"
},
"dropout": 0.25,
"dtype": "float32",
"id2label": {
"0": "LABEL_0"
},
"label2id": {
"LABEL_0": 0
},
"model_type": "fuse_matcher",
"transformers_version": "5.18.0",
"vocab_size": 4433
}
|