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ファームウェアの初期化
ディップスイッチ＆ピン切り替え
Qwen3-VL-2B-Instruct
- モデルを手動でダウンロードし、raspberrypi5 にアップロードするか、以下のコマンドでモデルリポジトリを取得します。
ヒント
git lfs がインストールされていない場合は、git lfs インストール手順を参照してインストールしてください。
git clone https://huggingface.co/M5Stack/Qwen3-VL-2B-Instruct-axmodelファイルの説明
m5stack@raspberrypi:~/rsp/Qwen3-VL-2B-Instruct-axmodel $ ls -lh
total 7.4M
drwxrwxr-x 2 m5stack m5stack 4.0K Oct 28 09:37 images
-rwxrwxr-x 1 m5stack m5stack 7.3M Nov 7 15:55 main_axcl_aarch64
-rwxrwxr-x 1 m5stack m5stack 276 Nov 7 11:58 post_config.json
drwxrwxr-x 2 m5stack m5stack 4.0K Oct 28 09:38 Qwen3-VL-2B-Instruct-ax8850
drwxrwxr-x 2 m5stack m5stack 4.0K Oct 28 09:31 qwen3-vl-tokenizer
-rw-rw-r-- 1 m5stack m5stack 24 Nov 7 14:12 README.md
-rwxrwxr-x 1 m5stack m5stack 715 Nov 7 14:17 run_image_axcl_aarch64.sh
-rwxrwxr-x 1 m5stack m5stack 715 Nov 7 14:17 run_video_axcl_aarch64.sh
-rwxrwxr-x 1 m5stack m5stack 9.4K Nov 7 14:42 tokenizer_images.py
-rwxrwxr-x 1 m5stack m5stack 9.3K Nov 7 14:41 tokenizer_video.py
drwxrwxr-x 2 m5stack m5stack 4.0K Nov 7 11:26 videoヒント
すでに qwen 仮想環境を作成済みの場合は、再作成する必要はありません。アクティベートするだけでOKです。
- 仮想環境を作成します。
python -m venv qwen- 仮想環境をアクティベートします。
source qwen/bin/activate- 依存パッケージをインストールします。
pip install transformers jinja2- 画像用 tokenizer パーサーを起動します。
python tokenizer_images.py - 画像 tokenizer サービスを実行します。Host IP はデフォルトで localhost、ポートは 8080 に設定されます。実行後の出力例は以下の通りです。
(qwen) m5stack@raspberrypi:~/rsp/Qwen3-VL-2B-Instruct-axmodel $ python tokenizer_images.py
None None 151645 <|im_end|>
[151644, 8948, 198, 2610, 525, 264, 10950, 17847, 13, 151645, 198, 151644, 872, 198, 151652, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151653, 74785, 419, 2168, 13, 151645, 198, 151644, 77091, 198]
281
[151644, 8948, 198, 2610, 525, 264, 10950, 17847, 13, 151645, 198, 151644, 872, 198, 14990, 1879, 151645, 198, 151644, 77091, 198]
21
http://localhost:8080ヒント
以下の操作は、新しい raspberrypi のターミナルを開いて実行してください。
- 実行権限を付与します。
chmod +x main_axcl_aarch64 run_image_axcl_aarch64.sh- Qwen3 モデルの画像推論サービスを起動します。
./run_image_axcl_aarch64.sh起動成功後は以下のように表示されます。
m5stack@raspberrypi:~/rsp/Qwen3-VL-2B-Instruct-axmodel $ ./run_image_axcl_aarch64.sh
[I][ Init][ 163]: LLM init start
[I][ Init][ 34]: connect http://127.0.0.1:8080 ok
bos_id: -1, eos_id: 151645
img_start_token: 151652
img_context_token: 151655
3% | ██ | 1 / 31 [0.01s<0.19s, 166.67 count/s] tokenizer init ok[I][ Init][ 45]: LLaMaEmbedSelector use mmap
6% | ███ | 2 / 31 [0.01s<0.09s, 333.33 count/s] embed_selector init ok
[I][ run][ 30]: AXCLWorker start with devid 0
80% | ███████████████████████████████████████████████ █ █ | 24 / 31 [45.28s<56.14s, 0.55 count/s] init 26 axmodel ok,devid(0) rem100% | ████████████████████████████████ | 31 / 31 [61.71s<61.71s, 0.50 count/s] init post axmodel ok,remain_cmm(3341 MB)3665 MB)
input size: 1
name: hidden_states [unknown] [unknown]
1 x 576 x 512 x 3 size:884736
output size: 4
name: hidden_states_out
144 x 2048 size:1179648
name: deepstack_feature_0
144 x 2048 size:1179648
name: deepstack_feature_1
144 x 2048 size:1179648
name: deepstack_feature_2
144 x 2048 size:1179648
[I][ Init][ 268]: IMAGE_CONTEXT_TOKEN: 151655, IMAGE_START_TOKEN: 151652
[I][ Init][ 329]: image encoder output float32
[I][ Init][ 341]: max_token_len : 2047
[I][ Init][ 344]: kv_cache_size : 1024, kv_cache_num: 2047
[I][ Init][ 352]: prefill_token_num : 128
[I][ Init][ 356]: grp: 1, prefill_max_token_num : 1
[I][ Init][ 356]: grp: 2, prefill_max_token_num : 128
[I][ Init][ 356]: grp: 3, prefill_max_token_num : 256
[I][ Init][ 356]: grp: 4, prefill_max_token_num : 384
[I][ Init][ 356]: grp: 5, prefill_max_token_num : 512
[I][ Init][ 356]: grp: 6, prefill_max_token_num : 640
[I][ Init][ 356]: grp: 7, prefill_max_token_num : 768
[I][ Init][ 356]: grp: 8, prefill_max_token_num : 896
[I][ Init][ 356]: grp: 9, prefill_max_token_num : 1024
[I][ Init][ 356]: grp: 10, prefill_max_token_num : 1152
[I][ Init][ 360]: prefill_max_token_num : 1152
________________________
| ID| remain cmm(MB)|
========================
| 0| 2899|
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
[I][ load_config][ 282]: load config:
{
"enable_repetition_penalty": false,
"enable_temperature": true,
"enable_top_k_sampling": true,
"enable_top_p_sampling": false,
"penalty_window": 30,
"repetition_penalty": 1,
"temperature": 0.2,
"top_k": 10,
"top_p": 0.8
}
[I][ Init][ 457]: LLM init ok
Type "q" to exit, Ctrl+c to stop current running
prompt >> Describe the content of the image
image >> images/recoAll_attractions_1.jpg
[I][ EncodeImage][ 531]: pixel_values size 1
[I][ EncodeImage][ 532]: grid_h 24 grid_w 24
[I][ EncodeImage][ 580]: image encode time : 191.645004 ms, size : 1
[I][ Encode][ 622]: input_ids size:171
[I][ Encode][ 630]: offset 15
[I][ Encode][ 659]: img_embed.size:1, 294912
[I][ Encode][ 673]: out_embed size:350208
[I][ Encode][ 674]: input_ids size 171
[I][ Encode][ 676]: position_ids size:171
[I][ Run][ 698]: input token num : 171, prefill_split_num : 2
[I][ Run][ 732]: input_num_token:128
[I][ Run][ 732]: input_num_token:43
[I][ Run][ 909]: ttft: 596.82 ms
This is a photograph of the Great Pyramids of Giza, the three largest and most famous pyramids in the world, located in the Giza Plateau in Egypt. The image captures the pyramids under a clear blue sky, with the vast, sandy desert landscape surrounding them. The pyramids are constructed from large stone blocks, and their massive, stepped structures are clearly visible. In the foreground, a few small figures can be seen, providing a sense of scale to the immense structures. The image is a clear and detailed depiction of the iconic ancient monuments.
[N][ Run][1062]: hit eos,avg 7.80 token/s
prompt >> - images tokenizer パーサーを停止し、video tokenizer パーサーを起動します。
python tokenizer_video.py- video tokenizer サービスを実行します。Host IP はデフォルトで localhost、ポート番号は 8080 に設定されます。出力例は以下の通りです。
(qwen) m5stack@raspberrypi:~/rsp/Qwen3-VL-2B-Instruct-axmodel $ python tokenizer_video.py
None None 151645 <|im_end|>
[151644, 8948, 198, 2610, 525, 264, 10950, 17847, 13, 151645, 198, 151644, 872, 198, 151652, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151656, 151653, 74785, 419, 2168, 13, 151645, 198, 151644, 77091, 198]
281
[151644, 8948, 198, 2610, 525, 264, 10950, 17847, 13, 151645, 198, 151644, 872, 198, 14990, 1879, 151645, 198, 151644, 77091, 198]
21
http://localhost:8080- Qwen3 モデルの動画推論サービスを起動します。
./run_video_axcl_aarch64.sh起動成功後の例：
m5stack@raspberrypi:~/rsp/Qwen3-VL-2B-Instruct-axmodel $ ./run_video_axcl_aarch64.sh
[I][ Init][ 163]: LLM init start
[I][ Init][ 34]: connect http://127.0.0.1:8080 ok
bos_id: -1, eos_id: 151645
img_start_token: 151652
img_context_token: 151656
3% | ██ | 1 / 31 [0.00s<0.09s, 333.33 count/s] tokenizer init ok[I][ Init][ 45]: LLaMaEmbedSelector use mmap
6% | ███ | 2 / 31 [0.00s<0.06s, 500.00 count/s] embed_selector init ok
[I][ run][ 30]: AXCLWorker start with devid 0
16% | █████████ ██ | 4 / 31 [6.09s<47.22s, 0.66 count/s] init 7 axmodel ok,devid(0) remain_cmm(-1 MB 93% | ███████████████████████████████████████████████████████████ | 29 / 31 [39.21s<43.41s, 0.71 count/s] init 13 axmodel ok,devid(0) r100% | ████████████████████████████████ | 31 / 31 [45.05s<46.55s, 0.67 count/s] init post axmodel ok,remain_cmm(3341 MB)3665 MB)
input size: 1
name: hidden_states [unknown] [unknown]
1 x 576 x 512 x 3 size:884736
output size: 4
name: hidden_states_out
144 x 2048 size:1179648
name: deepstack_feature_0
144 x 2048 size:1179648
name: deepstack_feature_1
144 x 2048 size:1179648
name: deepstack_feature_2
144 x 2048 size:1179648
[I][ Init][ 268]: IMAGE_CONTEXT_TOKEN: 151656, IMAGE_START_TOKEN: 151652
[I][ Init][ 329]: image encoder output float32
[I][ Init][ 341]: max_token_len : 2047
[I][ Init][ 344]: kv_cache_size : 1024, kv_cache_num: 2047
[I][ Init][ 352]: prefill_token_num : 128
[I][ Init][ 356]: grp: 1, prefill_max_token_num : 1
[I][ Init][ 356]: grp: 2, prefill_max_token_num : 128
[I][ Init][ 356]: grp: 3, prefill_max_token_num : 256
[I][ Init][ 356]: grp: 4, prefill_max_token_num : 384
[I][ Init][ 356]: grp: 5, prefill_max_token_num : 512
[I][ Init][ 356]: grp: 6, prefill_max_token_num : 640
[I][ Init][ 356]: grp: 7, prefill_max_token_num : 768
[I][ Init][ 356]: grp: 8, prefill_max_token_num : 896
[I][ Init][ 356]: grp: 9, prefill_max_token_num : 1024
[I][ Init][ 356]: grp: 10, prefill_max_token_num : 1152
[I][ Init][ 360]: prefill_max_token_num : 1152
________________________
| ID| remain cmm(MB)|
========================
| 0| 2899|
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
[I][ load_config][ 282]: load config:
{
"enable_repetition_penalty": false,
"enable_temperature": true,
"enable_top_k_sampling": true,
"enable_top_p_sampling": false,
"penalty_window": 30,
"repetition_penalty": 1,
"temperature": 0.2,
"top_k": 10,
"top_p": 0.8
}
[I][ Init][ 457]: LLM init ok
Type "q" to exit, Ctrl+c to stop current running
prompt >> Describe the content of the video
video >> video
video/out_0001.jpg
video/out_0002.jpg
video/out_0003.jpg
video/out_0004.jpg
video/out_0005.jpg
video/out_0006.jpg
video/out_0007.jpg
video/out_0008.jpg
video/out_0009.jpg
[I][ EncodeImage][ 531]: pixel_values size 5
[I][ EncodeImage][ 532]: grid_h 24 grid_w 24
[I][ EncodeImage][ 580]: image encode time : 915.744019 ms, size : 5
[I][ Encode][ 622]: input_ids size:747
[I][ Encode][ 630]: offset 15
[I][ Encode][ 659]: img_embed.size:5, 294912
[I][ Encode][ 664]: offset:159
[I][ Encode][ 664]: offset:303
[I][ Encode][ 664]: offset:447
[I][ Encode][ 664]: offset:591
[I][ Encode][ 673]: out_embed size:1529856
[I][ Encode][ 674]: input_ids size 747
[I][ Encode][ 676]: position_ids size:747
[I][ Run][ 698]: input token num : 747, prefill_split_num : 6
[I][ Run][ 732]: input_num_token:128
[I][ Run][ 732]: input_num_token:128
[I][ Run][ 732]: input_num_token:128
[I][ Run][ 732]: input_num_token:128
[I][ Run][ 732]: input_num_token:128
[I][ Run][ 732]: input_num_token:107
[I][ Run][ 909]: ttft: 2033.21 ms
The video captures a person walking through a modern, well-lit hallway. The individual, seen from behind, is wearing a white t-shirt with a blue graphic on the back and dark pants. They are moving towards a glass door, which is part of a larger set of doors, possibly in a building's entrance or a corridor.
The hallway features dark, polished tiles with a subtle, elegant pattern. A green emergency exit sign is visible on the wall, indicating the direction to the exit. To the right of the person, a laptop is placed on a stand, its screen displaying a blue image, possibly a video or a live feed. The laptop is connected to a cable, suggesting it might be used for monitoring or communication purposes.
The overall atmosphere of the scene is clean, professional, and modern, with a focus on safety and technology. The person's movement and the surrounding environment suggest a routine activity, such as entering a building or checking on a system.
[N][ Run][1062]: hit eos,avg 7.77 token/s
prompt >>