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.gitattributes

@@ -34,3 +34,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 *.axmodel filter=lfs diff=lfs merge=lfs -text
+main_api_ax650 filter=lfs diff=lfs merge=lfs -text
+main_api_axcl_aarch64 filter=lfs diff=lfs merge=lfs -text
+main_api_axcl_x86 filter=lfs diff=lfs merge=lfs -text
+main_ax650 filter=lfs diff=lfs merge=lfs -text
+main_axcl_aarch64 filter=lfs diff=lfs merge=lfs -text
+main_axcl_x86 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,202 @@
----
-license: mit
----
+---
+license: mit
+language:
+- zh
+- en
+base_model:
+- Qwen/Qwen2.5-3B-Instruct-GPTQ-INT8
+- Qwen/Qwen2.5-3B-Instruct-GPTQ-INT4
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- Context
+- Qwen2.5-3B-Instruct-GPTQ-INT8
+- Qwen2.5-3B-Instruct-GPTQ-INT4
+---
+
+# Qwen2.5-3B-Instruct
+
+This version of Qwen2.5-3B-Instruct has been converted to run on the Axera NPU using **w8a16** and **w4a16** quantization.
+
+This model has been optimized with the following LoRA: 
+
+Compatible with Pulsar2 version: 4.1
+
+## Feature
+
+- Support for longer contexts, in this sample it's 2k
+- Support context dialogue
+- System prompt kvcache is supported
+
+## Convert tools links:
+
+For those who are interested in model conversion, you can try to export axmodel through the original repo 
+
+[Pulsar2 Link, How to Convert LLM from Huggingface to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/appendix/build_llm.html) 
+
+[AXera NPU AXEngine LLM Runtime](https://github.com/AXERA-TECH/ax-llm/tree/ax-context) 
+
+[AXera NPU AXCL LLM Runtime](https://github.com/AXERA-TECH/ax-llm/tree/axcl-context) 
+
+### Convert script
+
+The follow show how to convert Qwen2.5-3B-Instruct-GPTQ-Int8
+
+```
+pulsar2 llm_build --input_path Qwen/Qwen2.5-3B-Instruct-GPTQ-Int8  \
+                  --output_path Qwen/Qwen2.5-3B-Instruct-GPTQ-Int8-ctx-ax650 \
+                  --hidden_state_type bf16 --kv_cache_len 2047 --prefill_len 128 \
+                  --last_kv_cache_len 128 \
+                  --last_kv_cache_len 256 \
+                  --last_kv_cache_len 384 \
+                  --last_kv_cache_len 512 \
+                  --last_kv_cache_len 640 \
+                  --last_kv_cache_len 768 \
+                  --last_kv_cache_len 896 \
+                  --last_kv_cache_len 1024 \
+                  --chip AX650 -c 1 --parallel 8
+```
+
+## Support Platform
+
+- AX650
+  - AX650N DEMO Board
+  - [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html)
+  - [M.2 Accelerator card](https://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html)
+  
+  
+
+|Chips|w8a16|w4a16| DDR(w8) | Flash(w8) | DDR(w4) | Flash(w4) |
+|--|--|--|--|--|--|--|
+|AX650|  |  |  |  | 2.8GB | 2.9GB |
+
+## How to use
+
+Download all files from this repository to the device
+
+```
+(base) axera@raspberrypi:~/samples/AXERA-TECH/Qwen2.5-3B-Instruct $ tree -L 1
+.
+├── config.json
+├── main_api_ax650
+├── main_api_axcl_aarch64
+├── main_api_axcl_x86
+├── main_ax650
+├── main_axcl_aarch64
+├── main_axcl_x86
+├── post_config.json
+├── qwen2.5-3b-ctx-int4-ax650
+├── qwen2.5_tokenizer
+├── qwen2.5_tokenizer_uid.py
+├── README.md
+├── run_qwen2.5_3b_ctx_ax650.sh
+├── run_qwen2.5_3b_ctx_axcl_aarch64.sh
+├── run_qwen2.5_3b_ctx_axcl_x86.sh
+├── run_qwen2.5_3b_ctx_int4_ax650.sh
+├── run_qwen2.5_3b_ctx_int4_axcl_aarch64.sh
+└── run_qwen2.5_3b_ctx_int4_axcl_x86.sh
+
+3 directories, 16 files
+```
+
+#### Start the Tokenizer service
+
+```
+(py312) axera@raspberrypi:~/samples/AXERA-TECH/Qwen2.5-3B-Instruct $ python qwen2.5_tokenizer_uid.py
+None of PyTorch, TensorFlow >= 2.0, or Flax have been found. Models won't be available and only tokenizers, configuration and file/data utilities can be used.
+Server running at http://0.0.0.0:12345
+```
+
+#### System prompt cache
+
+- The System prompt can be preset through the configuration file from `--system_prompt`
+- The System prompt can be cached in the form of kv cache to a specified folder for quick loading at the next run time from `--kvcache_path`
+- This folder needs to be created manually before running, for example `mkdir kvcache`
+
+```
+./main_axcl_aarch64 \
+--template_filename_axmodel "qwen2.5-3b-ctx-int4-ax650/qwen2_p128_l%d_together.axmodel" \
+--axmodel_num 36 \
+--url_tokenizer_model "http://127.0.0.1:12345" \
+--filename_post_axmodel "qwen2.5-3b-ctx-int4-ax650/qwen2_post.axmodel" \
+--filename_tokens_embed "qwen2.5-3b-ctx-int4-ax650/model.embed_tokens.weight.bfloat16.bin" \
+--tokens_embed_num 151936 \
+--tokens_embed_size 2048 \
+--use_mmap_load_embed 1 \
+--live_print 1 \
+--devices 0
+
+#--system_prompt "你的名字叫小智（allen）,你是一个人畜无害的AI助手。深圳市今天（4月1日）阴天，愚人节，气温在14°C至19°C之间，微风。" \
+#--kvcache_path "./kvcache" \
+```
+
+#### Inference with AX650 Host, such as M4N-Dock(爱芯派Pro) or AX650N DEMO Board
+
+Open another terminal and run `run_qwen2.5_3b_ctx_ax650.sh`
+
+TODO
+
+#### Inference with M.2 Accelerator card
+
+[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.
+
+```
+(base) axera@raspberrypi:~/samples/AXERA-TECH/Qwen2.5-3B-Instruct $ ./run_qwen2.5_3b_ctx_int4_axcl_aarch64.sh
+[I][                            Init][ 130]: LLM init start
+[I][                            Init][  34]: connect http://127.0.0.1:12345 ok
+[I][                            Init][  57]: uid: ec8f8194-c12f-41fa-b1a0-1ae232c9f15a
+bos_id: -1, eos_id: 151645
+  2% | █                                 |   1 /  39 [0.55s<21.33s, 1.83 count/s] tokenizer init ok[I][                            Init][  45]: LLaMaEmbedSelector use mmap
+  5% | ██                                |   2 /  39 [0.55s<10.67s, 3.66 count/s] embed_selector init ok
+[I][                             run][  30]: AXCLWorker start with devid 0
+ 76% | ██████████████████████████████████████████████  █       ██  |  29 /  39 [41.68s<58.05s, 0.67 count/s] init 6 axmodel ok,devid(0) remain_cmm(-1 MB)        |  30 /  39 [41.6100% | ████████████████████████████████ |  39 /  39 [61.29s<64.60s, 0.60 count/s] init post axmodel ok,remain_cmm(3981 MB)4305 MB)
+[I][                            Init][ 221]: max_token_len : 2047
+[I][                            Init][ 224]: kv_cache_size : 256, kv_cache_num: 2047
+[I][                            Init][ 232]: prefill_token_num : 128
+[I][                            Init][ 236]: grp: 1, prefill_max_token_num : 1
+[I][                            Init][ 236]: grp: 2, prefill_max_token_num : 128
+[I][                            Init][ 236]: grp: 3, prefill_max_token_num : 256
+[I][                            Init][ 236]: grp: 4, prefill_max_token_num : 384
+[I][                            Init][ 236]: grp: 5, prefill_max_token_num : 512
+[I][                            Init][ 236]: grp: 6, prefill_max_token_num : 640
+[I][                            Init][ 236]: grp: 7, prefill_max_token_num : 768
+[I][                            Init][ 236]: grp: 8, prefill_max_token_num : 896
+[I][                            Init][ 236]: grp: 9, prefill_max_token_num : 1024
+[I][                            Init][ 240]: prefill_max_token_num : 1024
+________________________
+|    ID| remain cmm(MB)|
+========================
+|     0|           3981|
+¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
+[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": 20,
+    "repetition_penalty": 1.2,
+    "temperature": 0.9,
+    "top_k": 10,
+    "top_p": 0.8
+}
+
+[I][                            Init][ 263]: LLM init ok
+Type "q" to exit, Ctrl+c to stop current running
+[I][          GenerateKVCachePrefill][ 324]: input token num : 21, prefill_split_num : 1 prefill_grpid : 2
+[I][          GenerateKVCachePrefill][ 367]: input_num_token:21
+[I][                            main][ 234]: precompute_len: 21
+[I][                            main][ 235]: system_prompt: You are Qwen, created by Alibaba Cloud. You are a helpful assistant.
+prompt >> who are you
+[I][                      SetKVCache][ 614]: prefill_grpid:2 kv_cache_num:128 precompute_len:21 input_num_token:11
+[I][                      SetKVCache][ 617]: current prefill_max_token_num:896
+[I][                             Run][ 855]: input token num : 11, prefill_split_num : 1
+[I][                             Run][ 887]: input_num_token:11
+[I][                             Run][1016]: ttft: 596.11 ms
+I am Qwen, created by Alibaba Cloud. I am here to assist with a wide range of tasks and answer a variety of questions. How can I assist you today?
+
+[N][                             Run][1168]: hit eos,avg 7.72 token/s
+
+[I][                      GetKVCache][ 583]: precompute_len:67, remaining:957
+prompt >> q
+```

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post_config.json

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+    "enable_temperature" : true,
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+    
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+    "repetition_penalty" : 1.2,
+    "penalty_window" : 20,
+
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+    "top_p" : 0.8,
+
+    "enable_top_k_sampling" : true,
+    "top_k" : 10
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