Instructions to use OpenGVLab/InternViT-6B-224px with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/InternViT-6B-224px with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="OpenGVLab/InternViT-6B-224px", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenGVLab/InternViT-6B-224px", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 746 Bytes
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"_name_or_path": "./",
"architectures": [
"InternVisionModel"
],
"auto_map": {
"AutoConfig": "configuration_intern_vit.InternVisionConfig",
"AutoModel": "modeling_intern_vit.InternVisionModel"
},
"attention_dropout": 0.0,
"drop_path_rate": 0.0,
"dropout": 0.0,
"hidden_act": "gelu",
"hidden_size": 3200,
"image_size": 224,
"initializer_factor": 0.1,
"initializer_range": 1e-10,
"intermediate_size": 12800,
"layer_norm_eps": 1e-06,
"model_type": "intern_vit_6b",
"num_attention_heads": 25,
"num_channels": 3,
"num_hidden_layers": 48,
"patch_size": 14,
"qk_normalization": true,
"qkv_bias": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.32.0",
"use_flash_attn": true
}
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