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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model:
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- HuggingFaceTB/SmolLM2-360M-Instruct
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tags:
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- HuggingFaceTB
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- SmolLM2
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- SmolLM2-360M-Instruct
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- Int8
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- M5Stack
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- RaspberryPi 5
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language:
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- en
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---
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# SmolLM2-360M-Instruct
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This version of SmolLM2-360M-Instruct has been converted to run on the Axera NPU using **w8a16** quantization.
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This model has been optimized with the following LoRA:
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Compatible with Pulsar2 version: 3.4(Not released yet)
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## Convert tools links:
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For those who are interested in model conversion, you can try to export axmodel through the original repo
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https://huggingface.co/HuggingFaceTB/SmolLM2-360M-Instruct
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[Pulsar2 Link, How to Convert LLM from Huggingface to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/appendix/build_llm.html)
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[AXera NPU HOST LLM Runtime](https://github.com/AXERA-TECH/ax-llm/tree/internvl2)
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[AXera NPU AXCL LLM Runtime](https://github.com/AXERA-TECH/ax-llm/tree/axcl-llm-internvl)
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## Support Platform
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- AX650
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- AX650N DEMO Board
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- [M4N-Dock(η±θ―ζ΄ΎPro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html)
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- [M.2 Accelerator card](https://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html)
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- AX630C
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- [η±θ―ζ΄Ύ2](https://axera-pi-2-docs-cn.readthedocs.io/zh-cn/latest/index.html)
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- [Module-LLM](https://docs.m5stack.com/zh_CN/module/Module-LLM)
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- [LLM630 Compute Kit](https://docs.m5stack.com/zh_CN/core/LLM630%20Compute%20Kit)
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|Chips|w8a16|w4a16|
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|--|--|--|
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|AX650| 39 tokens/sec|todo|
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|AX630C| 14 tokens/sec|todo|
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## How to use
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Download all files from this repository to the device
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```
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root@ax650:/mnt/qtang/llm-test/smollm2-360m# tree -L 1
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.
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|-- main_axcl_aarch64
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|-- main_axcl_x86
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|-- main_prefill
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|-- post_config.json
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|-- run_smollm2_360m_ax630c.sh
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|-- run_smollm2_360m_ax650.sh
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|-- run_smollm2_360m_axcl_aarch64.sh
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|-- run_smollm2_360m_axcl_x86.sh
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|-- smollm2-360m-ax630c
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|-- smollm2-360m-ax650
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|-- smollm2_tokenizer
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`-- smollm2_tokenizer.py
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```
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### Install transformer
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```
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pip install transformers==4.41.1
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```
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### Start the Tokenizer service
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```
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root@ax650:/mnt/qtang/llm-test/smollm2-360m$ python smollm2_tokenizer.py --port 12345
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1 <|im_start|> 2 <|im_end|>
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<|im_start|>system
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You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
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<|im_start|>user
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hello world<|im_end|>
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<|im_start|>assistant
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[1, 9690, 198, 2683, 359, 253, 5356, 5646, 11173, 3365, 3511, 308, 34519, 28, 7018, 411, 407, 19712, 8182, 2, 198, 1, 4093, 198, 28120, 905, 2, 198, 1, 520, 9531, 198]
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http://localhost:12345
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```
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### Inference with AX650 Host, such as M4N-Dock(η±θ―ζ΄ΎPro) or AX650N DEMO Board
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Open another terminal and run `run_smollm2_360m_ax650.sh`
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```
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root@ax650:/mnt/qtang/llm-test/smollm2-360m# ./run_smollm2_360m_ax650.sh
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[I][ Init][ 125]: LLM init start
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bos_id: 1, eos_id: 2
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2% | β | 1 / 35 [0.00s<0.14s, 250.00 count/s] tokenizer init ok
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[I][ Init][ 26]: LLaMaEmbedSelector use mmap
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100% | ββββββββββββββββββββββββββββββββ | 35 / 35 [0.81s<0.81s, 43.37 count/s] init post axmodel ok,remain_cmm(3339 MB)
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[I][ Init][ 241]: max_token_len : 1023
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[I][ Init][ 246]: kv_cache_size : 320, kv_cache_num: 1023
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[I][ Init][ 254]: prefill_token_num : 128
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[I][ load_config][ 281]: load config:
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{
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"enable_repetition_penalty": false,
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"enable_temperature": true,
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"enable_top_k_sampling": true,
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"enable_top_p_sampling": false,
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"penalty_window": 20,
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"repetition_penalty": 1.2,
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"temperature": 0.9,
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"top_k": 10,
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"top_p": 0.8
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}
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[I][ Init][ 268]: LLM init ok
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Type "q" to exit, Ctrl+c to stop current running
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>> who are you?
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[I][ Run][ 466]: ttft: 156.63 ms
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I'm a chatbot developed by the Artificial Intelligence Research and Development Lab (AI R&D Lab) at Hugging Face Labs,
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specifically designed to facilitate and augment human-AI conversations. My role is to provide assistance in understanding
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and responding to natural language queries, using advanced language models and AI algorithms to understand context and intent.
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[N][ Run][ 605]: hit eos,avg 38.70 token/s
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>> q
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```
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### Inference with M.2 Accelerator card
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[What is M.2 Accelerator card?](https://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html), Show this DEMO based on Raspberry PI 5.
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```
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(base) axera@raspberrypi:~/samples/smollm2-360m $ ./run_smollm2_360m_axcl_aarch64.sh
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build time: Feb 13 2025 15:44:57
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[I][ Init][ 111]: LLM init start
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bos_id: 1, eos_id: 2
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100% | ββββββοΏ½οΏ½οΏ½βββββββββββββββββββββββββ | 35 / 35 [18.07s<18.07s, 1.94 count/s] init post axmodel okremain_cmm(6621 MB)
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[I][ Init][ 226]: max_token_len : 1023
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[I][ Init][ 231]: kv_cache_size : 320, kv_cache_num: 1023
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[I][ load_config][ 282]: load config:
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{
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"enable_repetition_penalty": false,
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"enable_temperature": true,
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"enable_top_k_sampling": true,
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"enable_top_p_sampling": false,
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"penalty_window": 20,
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"repetition_penalty": 1.2,
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"temperature": 0.9,
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"top_k": 10,
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"top_p": 0.8
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}
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[I][ Init][ 288]: LLM init ok
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Type "q" to exit, Ctrl+c to stop current running
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>> who are you?
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I'm a virtual AI assistant, designed to support users with their questions and tasks.
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I was trained on a vast dataset of text, including text from various sources and
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conversations. This extensive training allows me to understand and respond to a wide range of queries.
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I'm here to be helpful and provide answers to your questions.
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[N][ Run][ 610]: hit eos,avg 20.81 token/s
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>> ^Cq
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(base) axera@raspberrypi:~ $ axcl-smi
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+------------------------------------------------------------------------------------------------+
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| AXCL-SMI V2.26.0_20250205130139 Driver V2.26.0_20250205130139 |
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+-----------------------------------------+--------------+---------------------------------------+
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| Card Name Firmware | Bus-Id | Memory-Usage |
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| Fan Temp Pwr:Usage/Cap | CPU NPU | CMM-Usage |
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|=========================================+==============+=======================================|
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| 0 AX650N V2.26.0 | 0000:01:00.0 | 171 MiB / 945 MiB |
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| -- 39C -- / -- | 2% 0% | 468 MiB / 7040 MiB |
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+-----------------------------------------+--------------+---------------------------------------+
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+------------------------------------------------------------------------------------------------+
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| Processes: |
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| Card PID Process Name NPU Memory Usage |
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|================================================================================================|
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| 0 18636 /home/axera/qtang/llm-test/smollm2-360m/main_axcl_aarch64 418580 KiB |
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+------------------------------------------------------------------------------------------------+
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(base) axera@raspberrypi:~ $
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```
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