Visual Document Retrieval
Transformers
Safetensors
ColPali
English
ultravbert
fill-mask
ultrabert
vision-language
multimodal
document-retrieval
vidore
custom_code
Instructions to use hf-internal-testing/testing-dummy-UltraVBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/testing-dummy-UltraVBERT with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMaskedLM processor = AutoProcessor.from_pretrained("hf-internal-testing/testing-dummy-UltraVBERT", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/testing-dummy-UltraVBERT", trust_remote_code=True, device_map="auto") - ColPali
How to use hf-internal-testing/testing-dummy-UltraVBERT with ColPali:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 2,838 Bytes
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"architectures": [
"UltraVBertForMaskedLM"
],
"auto_map": {
"AutoConfig": "configuration_ultravbert.UltraVBertConfig",
"AutoModel": "modeling_ultravbert.UltraVBertModel",
"AutoModelForMaskedLM": "modeling_ultravbert.UltraVBertForMaskedLM",
"AutoModelForSequenceClassification": "modeling_ultravbert.UltraVBertForSequenceClassification",
"AutoModelForTokenClassification": "modeling_ultravbert.UltraVBertForTokenClassification"
},
"classifier_dropout": 0.0,
"classifier_pooling": "cls",
"connector_norm": true,
"dtype": "bfloat16",
"image_token_id": 49191,
"initializer_cutoff_factor": 2.0,
"initializer_range": 0.02,
"model_type": "ultravbert",
"pixel_shuffle_factor": 4,
"text_config": {
"architectures": [
"UltrabertForMaskedLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 0,
"classifier_dropout": 0.0,
"classifier_pooling": "cls",
"dtype": "float32",
"eos_token_id": 0,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 1024,
"layer_types": [
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"full_attention"
],
"max_position_embeddings": 32768,
"mlp_bias": false,
"model_type": "ultrabert",
"num_attention_heads": 6,
"num_hidden_layers": 24,
"num_key_value_heads": 6,
"pad_token_id": 0,
"prediction_head_size": 768,
"rms_norm_eps": 1e-06,
"rope_parameters": {
"full_attention": {
"rope_theta": 2560000.0,
"rope_type": "default"
},
"sliding_attention": {
"rope_theta": 10000.0,
"rope_type": "default"
}
},
"sliding_window": 128,
"tie_word_embeddings": false,
"use_cache": false,
"vocab_size": 49280
},
"tie_word_embeddings": false,
"transformers_version": "5.21.0.dev0",
"vision_config": {
"attention_dropout": 0.0,
"hidden_act": "gelu_pytorch_tanh",
"hidden_size": 768,
"image_size": 512,
"intermediate_size": 3072,
"layer_norm_eps": 1e-06,
"model_type": "siglip_vision_model",
"num_attention_heads": 12,
"num_channels": 3,
"num_hidden_layers": 12,
"patch_size": 16,
"vision_use_head": false
}
}
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