Instructions to use litert-community/vit-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use litert-community/vit-base-patch16-224 with LiteRT:
# 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
Download model_metadata.json from litert-community/vit-base-patch16-224: direct link, hf CLI and curl.
- Browser
- Download file 6.79 kB
-
https://huggingface.co/litert-community/vit-base-patch16-224/resolve/main/model_metadata.json
- Command line
-
hf download hf://litert-community/vit-base-patch16-224/model_metadata.json
-
curl -L -o model_metadata.json https://huggingface.co/litert-community/vit-base-patch16-224/resolve/main/model_metadata.json
6.79 kB
| { | |
| "format": "tflite", | |
| "source": { | |
| "repo_id": "google/vit-base-patch16-224", | |
| "revision": "3f49326eb077187dfe1c2a2bb15fbd74e6ab91e3", | |
| "url": "https://huggingface.co/google/vit-base-patch16-224", | |
| "license": "apache-2.0" | |
| }, | |
| "artifacts": [ | |
| { | |
| "file": "model_fp32.tflite", | |
| "precision": "fp32", | |
| "sha256": "34678efe841c83480730c5c62b206bb6e597bc3b0d463ac3691cf698aec2295b", | |
| "bytes": 346369792, | |
| "inputs": [ | |
| { | |
| "name": "g0::pixel_values", | |
| "shape": [ | |
| 1, | |
| 3, | |
| 224, | |
| 224 | |
| ], | |
| "dtype": "float32", | |
| "layout": "NCHW" | |
| } | |
| ], | |
| "outputs": [ | |
| { | |
| "name": "g0::linear_72", | |
| "shape": [ | |
| 1, | |
| 1000 | |
| ], | |
| "dtype": "float32", | |
| "semantics": "raw classifier logits" | |
| } | |
| ], | |
| "quantization": null, | |
| "layer_norm": { | |
| "operator": "STABLEHLO_COMPOSITE", | |
| "name": "odml.group_norm", | |
| "count": 25, | |
| "decomposition_dtype": "float32", | |
| "converter_default": true, | |
| "input_output_dtype": "float32" | |
| }, | |
| "graph": { | |
| "main_operators": 346, | |
| "main_conversion_boundaries": {}, | |
| "dead_operators": 0, | |
| "unused_constant_tensors": 0 | |
| } | |
| }, | |
| { | |
| "file": "model_a16w8.tflite", | |
| "precision": "a16w8", | |
| "sha256": "a0021a9b5f70422695639cc7343e8810b703fd6c788fcad4dff806ba4073e5b8", | |
| "bytes": 91658499, | |
| "inputs": [ | |
| { | |
| "name": "g0::pixel_values", | |
| "shape": [ | |
| 1, | |
| 3, | |
| 224, | |
| 224 | |
| ], | |
| "dtype": "float32", | |
| "layout": "NCHW" | |
| } | |
| ], | |
| "outputs": [ | |
| { | |
| "name": "g0::static_linear_72", | |
| "shape": [ | |
| 1, | |
| 1000 | |
| ], | |
| "dtype": "float32", | |
| "semantics": "raw classifier logits" | |
| } | |
| ], | |
| "quantization": { | |
| "quantizer": "torchao", | |
| "mode": "static", | |
| "export": "native_affine_transformer_regions", | |
| "scope": "all_fully_connected_layers_and_transformer_activation_regions", | |
| "fully_connected_count": 73, | |
| "activations": { | |
| "granularity": "per_tensor", | |
| "fully_connected_dtype": "int16", | |
| "attention_dtype": "int16", | |
| "residual_dtype": "int16", | |
| "layer_norm_interface_dtype": "int16" | |
| }, | |
| "weights": { | |
| "dtype": "int8", | |
| "granularity": "per_output_channel", | |
| "symmetric": true | |
| }, | |
| "bias_dtype": "int64", | |
| "model_input_dtype": "float32", | |
| "model_output_dtype": "float32", | |
| "accumulator_guard": { | |
| "explicit_input_bounds": false, | |
| "bounded_layers": 0 | |
| }, | |
| "floating_regions": [ | |
| "patch_embedding", | |
| "public_input_output", | |
| "layer_norm_fallback_decompositions" | |
| ], | |
| "integer_regions": [ | |
| "fully_connected", | |
| "attention_batch_matmul", | |
| "residual_add", | |
| "softmax", | |
| "gelu", | |
| "reshape", | |
| "transpose" | |
| ] | |
| }, | |
| "layer_norm": { | |
| "operator": "STABLEHLO_COMPOSITE", | |
| "name": "odml.group_norm", | |
| "count": 25, | |
| "decomposition_dtype": "float32", | |
| "converter_default": true, | |
| "input_output_dtype": "int16" | |
| }, | |
| "deployment_note": "Primary quantized option for the tested NPUs. No explicit accumulator input clipping; qualify accumulator behavior on other backends. CPU fallback can be slow; tested GPU IR importer lacks INT16 quantization.", | |
| "graph": { | |
| "main_operators": 275, | |
| "main_conversion_boundaries": { | |
| "float_to_integer": 1, | |
| "integer_to_float": 1 | |
| }, | |
| "dead_operators": 0, | |
| "unused_constant_tensors": 0 | |
| } | |
| }, | |
| { | |
| "file": "model_a8w8.tflite", | |
| "precision": "a8w8", | |
| "sha256": "58a49e8c32a90224cbe13b8ce2eaebfa38eb6ec545cee8736126ec907b4c98d4", | |
| "bytes": 91335728, | |
| "inputs": [ | |
| { | |
| "name": "g0::pixel_values", | |
| "shape": [ | |
| 1, | |
| 3, | |
| 224, | |
| 224 | |
| ], | |
| "dtype": "float32", | |
| "layout": "NCHW" | |
| } | |
| ], | |
| "outputs": [ | |
| { | |
| "name": "g0::static_linear_72", | |
| "shape": [ | |
| 1, | |
| 1000 | |
| ], | |
| "dtype": "float32", | |
| "semantics": "raw classifier logits" | |
| } | |
| ], | |
| "quantization": { | |
| "quantizer": "torchao", | |
| "mode": "static", | |
| "export": "native_affine_transformer_regions", | |
| "scope": "all_fully_connected_layers_and_transformer_activation_regions", | |
| "fully_connected_count": 73, | |
| "activations": { | |
| "granularity": "per_tensor", | |
| "fully_connected_dtype": "int8", | |
| "attention_dtype": "int16", | |
| "residual_dtype": "int16", | |
| "layer_norm_interface_dtype": "int16" | |
| }, | |
| "weights": { | |
| "dtype": "int8", | |
| "granularity": "per_output_channel", | |
| "symmetric": true | |
| }, | |
| "bias_dtype": "int32", | |
| "model_input_dtype": "float32", | |
| "model_output_dtype": "float32", | |
| "floating_regions": [ | |
| "patch_embedding", | |
| "public_input_output", | |
| "layer_norm_fallback_decompositions" | |
| ], | |
| "integer_regions": [ | |
| "fully_connected", | |
| "attention_batch_matmul", | |
| "residual_add", | |
| "softmax", | |
| "gelu", | |
| "reshape", | |
| "transpose" | |
| ], | |
| "accumulator_guard": { | |
| "explicit_input_bounds": false, | |
| "bounded_layers": 0 | |
| } | |
| }, | |
| "layer_norm": { | |
| "operator": "STABLEHLO_COMPOSITE", | |
| "name": "odml.group_norm", | |
| "count": 25, | |
| "decomposition_dtype": "float32", | |
| "converter_default": true, | |
| "input_output_dtype": "int16" | |
| }, | |
| "deployment_note": "Reference mixed INT8/INT16 model that may suit devices limited to 32-bit integer accumulation in fully connected kernels. Has a substantial accuracy tradeoff and retains INT16 regions; backend support must be verified.", | |
| "graph": { | |
| "main_operators": 372, | |
| "main_conversion_boundaries": { | |
| "float_to_integer": 1, | |
| "integer_to_integer": 97, | |
| "integer_to_float": 1 | |
| }, | |
| "dead_operators": 0, | |
| "unused_constant_tensors": 0 | |
| } | |
| } | |
| ], | |
| "preprocessing": { | |
| "config_file": "preprocessor_config.json", | |
| "library": "transformers", | |
| "backend": "pil" | |
| }, | |
| "labels_file": "labels.json", | |
| "gpu_compat": false | |
| } | |