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README.md
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tags:
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- npu
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- amd
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- llama3
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- Ryzen AI
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---
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@@ -14,4 +14,122 @@ 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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tags:
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- npu
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- amd
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- llama3.1
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- Ryzen AI
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---
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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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### 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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git lfs install
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git clone https://huggingface.co/dahara1/llama3.1-8b-Instruct-amd-npu
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cd llama3.1-8b-Instruct-amd-npu
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git lfs pull
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cd ..
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copy <your_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_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 = "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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