Comments (6)
是两个文件,具体是什么问题呢?
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转换的目的是为了适配pmx自己的RoPE逻辑,然后后续会为了适配量化做这一步转换。
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是两个文件,具体是什么问题呢?
怎么进一步转换成 onnx 或者 pmx 格式?用 ppl.llm.serving 启动,提升 pmx 或者 onnx 文件不存在
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怎么进一步转换成 onnx 或者 pmx 格式?用 ppl.llm.serving 启动,提升 pmx 或者 onnx 文件不存在
继续Export.py导出模型,就能获得onnx格式的文件
from ppl.pmx.
怎么进一步转换成 onnx 或者 pmx 格式?用 ppl.llm.serving 启动,提升 pmx 或者 onnx 文件不存在
继续Export.py导出模型,就能获得onnx格式的文件
试过了,继续 Export 导出模型,有大量的警告, Warning: The shape interface of opmx::XX(如 ParallelEmbedding、ColumnParallelLinear、Reshape等) type is missing,用转出来的 onnx 格式的文件启动 ppl_llm_server,提示 unsupported op: domain[opmx], type[ParallelEmbedding]
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@Flynn-Zh 更具体的可能需要问下 @Alcanderian or @Jzz24
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Related Issues (10)
- Use A10 to export llama 13B model OOM. HOT 1
- TYPO in “ppl.pmx/docs/operators/dynamic_batching/MultiHeadAttention.md” HOT 2
- 怎么转换其它模型 HOT 3
- 转换llama2 70B模型时遇到的问题 HOT 4
- baichuan13B static/dynamic batching 生成一定长度的句子之后结果出现分歧 HOT 1
- 补充RoPE2D dynamic batching算子文档
- 文档内显示支持qwen1.5,但实际转换报错。 HOT 1
- Good first issue HOT 3
- [LLaMA2-7b] Warning: The shape inference of opmx::ParallelEmbedding type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function. (function UpdateReliable) HOT 1
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