Comments (1)
Hello there! It's understandable that navigating specialized hardware backends can be a complex endeavor, particularly when it comes to customization. Typically, hardware manufacturers like Qualcomm offer dedicated support or provide open-source resources to facilitate integration and development efforts.
To assist you, here are a few avenues to consider:
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Qualcomm AI Hub: While not explicitly open-source, Qualcomm does maintain a repository of AI models which could serve as a starting point or offer valuable insights. You may explore it at https://aihub.qualcomm.com/models.
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Hugging Face Hub: Qualcomm has an active presence on the Hugging Face Hub, a popular hub for machine learning models. They've promised to share how-to guides for LLMs at https://huggingface.co/qualcomm/Llama-v2-7B-Chat/discussions/1.
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Community Efforts: There's also a promising initiative within the llama.cpp community, where developers are working on integrating support for Qualcomm backends. This effort, visible through https://www.github.com/ggerganov/llama.cpp/pull/6869, underscores the potential for compatibility despite the current lack of official open-source solutions.
In summary, while a readily available open-source solution tailored for Qualcomm hardware might not exist at this moment, exploring these resources and engaging with the active communities can pave the way towards achieving your integration goals. Keep in mind that staying updated with these platforms and communities can lead to new developments and potential solutions over time.
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Related Issues (20)
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- 💡 [REQUEST] - <使用ollama来调用qwen:14B时,怎么设置输出文本长度呢> HOT 1
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- File "finetune.py", line 412, in <module> train() File "finetune.py", line 384, in train model = get_peft_model(model, lora_config) File "/opt/conda/envs/qwen/lib/python3.8/site-packages/peft/mapping.py", line 123, in get_peft_model peft_config.base_model_name_or_path = model.__dict__.get("name_or_path", None) AttributeError: 'NoneType' object has no attribute '__dict__'[BUG] <title> HOT 2
- qwen 14b 不微调的情况下,问相同的问题,模型输出也不太一致,是为什么?温度已经设置成0了 HOT 2
- [BUG] <title>torch.cuda.OutOfMemoryError: CUDA out of memory. HOT 1
- Qwen pre_trained, 打印一下内容,就没有了,不确定是否训练完成 HOT 2
- [BUG] 转换Qwen1.5-14B报错 HOT 1
- 多轮对话训练数据格式组织 HOT 1
- [BUG] Questionable embedding feature shape extracted from Qwen-7B-Chat HOT 2
- [BUG] <title> 命令行运行参数解析错误
- 工具调用的时候,本来用户没有输入参数,但是模型会自动幻想参数 HOT 1
- [BUG] model的forward函数接收attention_mask的时候,若attention_mask[i, 0]==0,则序列i输出的logits全都是NaN值 HOT 4
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- [BUG] <title>全参数微调qwen-14b-chat时卡住 HOT 1
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