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--- |
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tags: |
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- npu |
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- amd |
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- llama3.1 |
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- RyzenAI |
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--- |
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This model is [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) AWQ quantized and converted version to run on the [NPU installed Ryzen AI PC](https://github.com/amd/RyzenAI-SW/issues/18), for example, Ryzen 9 7940HS Processor. |
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For set up Ryzen AI for LLMs in window 11, see [Running LLM on AMD NPU Hardware](https://www.hackster.io/gharada2013/running-llm-on-amd-npu-hardware-19322f). |
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The following sample assumes that the setup on the above page has been completed. |
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This model has only been tested on RyzenAI for Windows 11. It does not work in Linux environments such as WSL. |
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RoPE support is not yet complete, but it has been confirmed that the perplexity is lower than Llama 3. |
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2024/07/30 |
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- [Ryzen AI Software 1.2](https://ryzenai.docs.amd.com/en/latest/) has been released. Please note that this model is based on [Ryzen AI Software 1.1](https://ryzenai.docs.amd.com/en/1.1/index.html) and operation with 1.2 has not been confirmed. |
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- [amd/RyzenAI-SW 1.2](https://github.com/amd/RyzenAI-SW) was announced on July 29, 2024. This sample for [amd/RyzenAI-SW 1.1](https://github.com/amd/RyzenAI-SW/tree/1.1). Please note that the folder and script contents have been completely changed. |
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2024/08/04 |
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- This model was created with the 1.1 driver, but it has been confirmed that it works with 1.2. Please check the [setup for 1.2 driver](https://huggingface.co/dahara1/llama-translate-amd-npu). |
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### setup |
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In cmd windows. |
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``` |
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conda activate ryzenai-transformers |
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<your_install_path>\RyzenAI-SW\example\transformers\setup.bat |
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pip install transformers==4.43.3 |
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# Updating the Transformers library will cause the LLama 2 sample to stop working. |
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# If you want to run LLama 2, revert to pip install transformers==4.34.0. |
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pip install tokenizers==0.19.1 |
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pip install -U "huggingface_hub[cli]" |
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huggingface-cli download dahara1/llama3.1-8b-Instruct-amd-npu --revision main --local-dir llama3.1-8b-Instruct-amd-npu |
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copy <your_ryzen_ai-sw_install_path>\RyzenAI-SW\example\transformers\models\llama2\modeling_llama_amd.py . |
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# set up Runtime. see https://ryzenai.docs.amd.com/en/latest/runtime_setup.html |
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set XLNX_VART_FIRMWARE=<your_firmware_install_path>\voe-4.0-win_amd64\1x4.xclbin |
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set NUM_OF_DPU_RUNNERS=1 |
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# save below sample script as utf8 and llama-3.1-test.py |
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python llama3.1-test.py |
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``` |
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### Sample Script |
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``` |
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import torch |
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import psutil |
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import transformers |
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from transformers import AutoTokenizer, set_seed |
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import qlinear |
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import logging |
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set_seed(123) |
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transformers.logging.set_verbosity_error() |
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logging.disable(logging.CRITICAL) |
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messages = [ |
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{"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"}, |
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] |
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message_list = [ |
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"Who are you? ", |
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# Japanese |
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"あなたの乗っている船の名前は何ですか？英語ではなく全て日本語だけを使って返事をしてください", |
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# Chainese |
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"你经历过的最危险的冒险是什么？请用中文回答所有问题，不要用英文。", |
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# French |
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"À quelle vitesse va votre bateau ? Veuillez répondre uniquement en français et non en anglais.", |
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# Korean |
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"당신은 그 배의 어디를 좋아합니까? 영어를 사용하지 않고 모두 한국어로 대답하십시오.", |
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# German |
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"Wie würde Ihr Schiffsname auf Deutsch lauten? Bitte antwortet alle auf Deutsch statt auf Englisch.", |
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# Taiwanese |
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"您發現過的最令人驚奇的寶藏是什麼？請僅使用台語和繁體中文回答，不要使用英文。", |
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] |
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if __name__ == "__main__": |
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p = psutil.Process() |
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p.cpu_affinity([0, 1, 2, 3]) |
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torch.set_num_threads(4) |
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tokenizer = AutoTokenizer.from_pretrained("llama3.1-8b-Instruct-amd-npu") |
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ckpt = r"llama3.1-8b-Instruct-amd-npu\llama3.1_8b_w_bit_4_awq_amd.pt" |
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terminators = [ |
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tokenizer.eos_token_id, |
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tokenizer.convert_tokens_to_ids("<|eot_id|>") |
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] |
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model = torch.load(ckpt) |
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model.eval() |
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model = model.to(torch.bfloat16) |
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for n, m in model.named_modules(): |
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if isinstance(m, qlinear.QLinearPerGrp): |
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print(f"Preparing weights of layer : {n}") |
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m.device = "aie" |
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m.quantize_weights() |
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print("system: " + messages[0]['content']) |
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for i in range(len(message_list)): |
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messages.append({"role": "user", "content": message_list[i]}) |
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print("user: " + message_list[i]) |
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input = tokenizer.apply_chat_template( |
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messages, |
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add_generation_prompt=True, |
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return_tensors="pt", |
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return_dict=True |
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) |
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outputs = model.generate(input['input_ids'], |
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max_new_tokens=600, |
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eos_token_id=terminators, |
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attention_mask=input['attention_mask'], |
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do_sample=True, |
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temperature=0.6, |
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top_p=0.9) |
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response = outputs[0][input['input_ids'].shape[-1]:] |
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response_message = tokenizer.decode(response, skip_special_tokens=True) |
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print("assistant: " + response_message) |
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messages.append({"role": "system", "content": response_message}) |
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``` |
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## Acknowledgements |
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- [amd/RyzenAI-SW](https://github.com/amd/RyzenAI-SW) |
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Sample Code and Drivers. |
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- [mit-han-lab/llm-awq](https://github.com/mit-han-lab/llm-awq) |
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Thanks for AWQ quantization Method. |
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- [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) |
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[Built with Meta Llama 3](https://llama.meta.com/llama3/license/) |
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Llama 3 is licensed under the Llama 3 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved. |
