Visual Question Answering
Transformers
Safetensors
fga
visual-dialog
visdial
multimodal
attention
factor-graph-attention
Eval Results (legacy)
Instructions to use Idan/fga with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Idan/fga with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="Idan/fga")# Load model directly from transformers import FGAForVisualDialog model = FGAForVisualDialog.from_pretrained("Idan/fga", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 979 Bytes
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"architectures": [
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"hidden_cap_dim": 128,
"hidden_hist_dim": 128,
"hidden_img_dim": 2048,
"hidden_ques_dim": 512,
"initializer_type": "he",
"legacy_unary_dropout": false,
"lstm_initializer_type": "he",
"model_type": "fga",
"num_history_rounds": 9,
"num_options": 100,
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|