Instructions to use braintacles/brainblip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use braintacles/brainblip with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="braintacles/brainblip")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("braintacles/brainblip") model = AutoModelForMultimodalLM.from_pretrained("braintacles/brainblip", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 834 Bytes
4398c11 3fd9247 4398c11 67f086b 4398c11 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | {
"_name_or_path": "brainblip",
"architectures": [
"BlipForConditionalGeneration"
],
"image_text_hidden_size": 256,
"initializer_factor": 1.0,
"initializer_range": 0.02,
"label_smoothing": 0.0,
"logit_scale_init_value": 2.6592,
"model_type": "blip",
"projection_dim": 512,
"text_config": {
"encoder_hidden_size": 1024,
"initializer_factor": 1.0,
"model_type": "blip_text_model",
"num_attention_heads": 12
},
"torch_dtype": "float32",
"transformers_version": "4.41.2",
"vision_config": {
"dropout": 0.0,
"hidden_size": 1024,
"initializer_factor": 1.0,
"initializer_range": 0.02,
"intermediate_size": 4096,
"model_type": "blip_vision_model",
"num_attention_heads": 16,
"num_channels": 3,
"num_hidden_layers": 24
}
}
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