Hugging Face's logo

qualcomm
/
ConvNext-Tiny

Image Classification
PyTorch
LiteRT
bu_auto
android
Model card Files
xet
Community
qaihm-bot commited on
Commit
5b8dbb4
·
verified ·
1 Parent(s): f8bdb41

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +30 -29
README.md CHANGED
@@ -34,39 +34,39 @@ More details on model performance across various devices, can be found
34
 
35
  | Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
36
  |---|---|---|---|---|---|---|---|---|
37
- | ConvNext-Tiny | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 3.336 ms | 0 - 269 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
38
- | ConvNext-Tiny | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 3.918 ms | 1 - 299 MB | FP16 | NPU | [ConvNext-Tiny.so](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.so) |
39
- | ConvNext-Tiny | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 13.329 ms | 0 - 197 MB | FP16 | NPU | [ConvNext-Tiny.onnx](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.onnx) |
40
- | ConvNext-Tiny | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 2.442 ms | 0 - 37 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
41
- | ConvNext-Tiny | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 2.827 ms | 1 - 38 MB | FP16 | NPU | [ConvNext-Tiny.so](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.so) |
42
- | ConvNext-Tiny | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 9.85 ms | 5 - 64 MB | FP16 | NPU | [ConvNext-Tiny.onnx](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.onnx) |
43
- | ConvNext-Tiny | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 1.819 ms | 0 - 41 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
44
- | ConvNext-Tiny | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 2.453 ms | 0 - 41 MB | FP16 | NPU | Use Export Script |
45
- | ConvNext-Tiny | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 8.499 ms | 1 - 67 MB | FP16 | NPU | [ConvNext-Tiny.onnx](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.onnx) |
46
- | ConvNext-Tiny | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 3.315 ms | 0 - 329 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
47
- | ConvNext-Tiny | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 3.657 ms | 1 - 4 MB | FP16 | NPU | Use Export Script |
48
- | ConvNext-Tiny | SA7255P ADP | SA7255P | TFLITE | 96.797 ms | 0 - 36 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
49
- | ConvNext-Tiny | SA7255P ADP | SA7255P | QNN | 97.334 ms | 1 - 9 MB | FP16 | NPU | Use Export Script |
50
- | ConvNext-Tiny | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 3.344 ms | 0 - 249 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
51
- | ConvNext-Tiny | SA8255 (Proxy) | SA8255P Proxy | QNN | 3.63 ms | 1 - 3 MB | FP16 | NPU | Use Export Script |
52
- | ConvNext-Tiny | SA8295P ADP | SA8295P | TFLITE | 11.111 ms | 0 - 37 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
53
- | ConvNext-Tiny | SA8295P ADP | SA8295P | QNN | 9.508 ms | 1 - 15 MB | FP16 | NPU | Use Export Script |
54
- | ConvNext-Tiny | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 3.336 ms | 0 - 319 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
55
- | ConvNext-Tiny | SA8650 (Proxy) | SA8650P Proxy | QNN | 3.658 ms | 1 - 3 MB | FP16 | NPU | Use Export Script |
56
- | ConvNext-Tiny | SA8775P ADP | SA8775P | TFLITE | 5.753 ms | 0 - 37 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
57
- | ConvNext-Tiny | SA8775P ADP | SA8775P | QNN | 6.196 ms | 1 - 11 MB | FP16 | NPU | Use Export Script |
58
- | ConvNext-Tiny | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 9.798 ms | 0 - 37 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
59
- | ConvNext-Tiny | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 10.379 ms | 1 - 37 MB | FP16 | NPU | Use Export Script |
60
- | ConvNext-Tiny | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 4.975 ms | 1 - 1 MB | FP16 | NPU | Use Export Script |
61
- | ConvNext-Tiny | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 16.257 ms | 58 - 58 MB | FP16 | NPU | [ConvNext-Tiny.onnx](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.onnx) |
62
 
63
 
64
 
65
 
66
  ## Installation
67
 
68
- This model can be installed as a Python package via pip.
69
 
 
70
  ```bash
71
  pip install qai-hub-models
72
  ```
@@ -123,7 +123,7 @@ ConvNext-Tiny
123
  Device : Samsung Galaxy S23 (13)
124
  Runtime : TFLITE
125
  Estimated inference time (ms) : 3.3
126
- Estimated peak memory usage (MB): [0, 269]
127
  Total # Ops : 328
128
  Compute Unit(s) : NPU (328 ops)
129
  ```
@@ -150,7 +150,7 @@ from qai_hub_models.models.convnext_tiny import Model
150
  torch_model = Model.from_pretrained()
151
 
152
  # Device
153
- device = hub.Device("Samsung Galaxy S23")
154
 
155
  # Trace model
156
  input_shape = torch_model.get_input_spec()
@@ -242,7 +242,8 @@ Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
242
 
243
 
244
  ## License
245
- * The license for the original implementation of ConvNext-Tiny can be found [here](https://github.com/pytorch/vision/blob/main/LICENSE).
 
246
  * The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)
247
 
248
 
 
34
 
35
  | Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
36
  |---|---|---|---|---|---|---|---|---|
37
+ | ConvNext-Tiny | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 3.346 ms | 0 - 249 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
38
+ | ConvNext-Tiny | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 3.922 ms | 1 - 299 MB | FP16 | NPU | [ConvNext-Tiny.so](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.so) |
39
+ | ConvNext-Tiny | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 13.362 ms | 0 - 188 MB | FP16 | NPU | [ConvNext-Tiny.onnx](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.onnx) |
40
+ | ConvNext-Tiny | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 2.456 ms | 0 - 41 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
41
+ | ConvNext-Tiny | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 2.817 ms | 1 - 42 MB | FP16 | NPU | [ConvNext-Tiny.so](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.so) |
42
+ | ConvNext-Tiny | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 9.678 ms | 1 - 61 MB | FP16 | NPU | [ConvNext-Tiny.onnx](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.onnx) |
43
+ | ConvNext-Tiny | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 2.11 ms | 0 - 40 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
44
+ | ConvNext-Tiny | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 2.104 ms | 1 - 41 MB | FP16 | NPU | Use Export Script |
45
+ | ConvNext-Tiny | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 8.385 ms | 1 - 67 MB | FP16 | NPU | [ConvNext-Tiny.onnx](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.onnx) |
46
+ | ConvNext-Tiny | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 3.339 ms | 0 - 279 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
47
+ | ConvNext-Tiny | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 3.692 ms | 1 - 3 MB | FP16 | NPU | Use Export Script |
48
+ | ConvNext-Tiny | SA7255P ADP | SA7255P | TFLITE | 96.596 ms | 0 - 36 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
49
+ | ConvNext-Tiny | SA7255P ADP | SA7255P | QNN | 97.188 ms | 1 - 10 MB | FP16 | NPU | Use Export Script |
50
+ | ConvNext-Tiny | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 3.336 ms | 0 - 259 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
51
+ | ConvNext-Tiny | SA8255 (Proxy) | SA8255P Proxy | QNN | 3.655 ms | 1 - 3 MB | FP16 | NPU | Use Export Script |
52
+ | ConvNext-Tiny | SA8295P ADP | SA8295P | TFLITE | 11.144 ms | 0 - 37 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
53
+ | ConvNext-Tiny | SA8295P ADP | SA8295P | QNN | 9.478 ms | 1 - 15 MB | FP16 | NPU | Use Export Script |
54
+ | ConvNext-Tiny | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 3.334 ms | 0 - 319 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
55
+ | ConvNext-Tiny | SA8650 (Proxy) | SA8650P Proxy | QNN | 3.663 ms | 1 - 3 MB | FP16 | NPU | Use Export Script |
56
+ | ConvNext-Tiny | SA8775P ADP | SA8775P | TFLITE | 5.706 ms | 0 - 36 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
57
+ | ConvNext-Tiny | SA8775P ADP | SA8775P | QNN | 6.216 ms | 1 - 11 MB | FP16 | NPU | Use Export Script |
58
+ | ConvNext-Tiny | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 9.768 ms | 0 - 37 MB | FP16 | NPU | [ConvNext-Tiny.tflite](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.tflite) |
59
+ | ConvNext-Tiny | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 10.423 ms | 1 - 38 MB | FP16 | NPU | Use Export Script |
60
+ | ConvNext-Tiny | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 3.922 ms | 1 - 1 MB | FP16 | NPU | Use Export Script |
61
+ | ConvNext-Tiny | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 16.225 ms | 58 - 58 MB | FP16 | NPU | [ConvNext-Tiny.onnx](https://huggingface.co/qualcomm/ConvNext-Tiny/blob/main/ConvNext-Tiny.onnx) |
62
 
63
 
64
 
65
 
66
  ## Installation
67
 
 
68
 
69
+ Install the package via pip:
70
  ```bash
71
  pip install qai-hub-models
72
  ```
 
123
  Device : Samsung Galaxy S23 (13)
124
  Runtime : TFLITE
125
  Estimated inference time (ms) : 3.3
126
+ Estimated peak memory usage (MB): [0, 249]
127
  Total # Ops : 328
128
  Compute Unit(s) : NPU (328 ops)
129
  ```
 
150
  torch_model = Model.from_pretrained()
151
 
152
  # Device
153
+ device = hub.Device("Samsung Galaxy S24")
154
 
155
  # Trace model
156
  input_shape = torch_model.get_input_spec()
 
242
 
243
 
244
  ## License
245
+ * The license for the original implementation of ConvNext-Tiny can be found
246
+ [here](https://github.com/pytorch/vision/blob/main/LICENSE).
247
  * The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)
248
 
249