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关于模型转换格式成 gguf #20

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HougeLangley opened this issue Apr 17, 2024 · 0 comments
Open

关于模型转换格式成 gguf #20

HougeLangley opened this issue Apr 17, 2024 · 0 comments

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@HougeLangley
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从 BlueZeros/MING-MOE-14B 下载了模型

git clone https://huggingface.co/BlueZeros/MING-MOE-14B ming

后续使用以下命令转换 lora 到 ggml 是成功的

(ollama) ╭─hougelangley at Arch-Legion in ~/ollama on main✘✘✘ 24-04-17 - 22:41:42
╰─(ollama) ⠠⠵ python llm/llama.cpp/convert-lora-to-ggml.py ./ming
model.layers.0.self_attn.k_proj => blk.0.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.0.self_attn.k_proj => blk.0.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.0.self_attn.o_proj => blk.0.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.0.self_attn.o_proj => blk.0.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.0.self_attn.q_proj => blk.0.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.0.self_attn.q_proj => blk.0.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.0.self_attn.v_proj => blk.0.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.0.self_attn.v_proj => blk.0.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.1.self_attn.k_proj => blk.1.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.1.self_attn.k_proj => blk.1.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.1.self_attn.o_proj => blk.1.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.1.self_attn.o_proj => blk.1.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.1.self_attn.q_proj => blk.1.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.1.self_attn.q_proj => blk.1.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.1.self_attn.v_proj => blk.1.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.1.self_attn.v_proj => blk.1.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.10.self_attn.k_proj => blk.10.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.10.self_attn.k_proj => blk.10.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.10.self_attn.o_proj => blk.10.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.10.self_attn.o_proj => blk.10.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.10.self_attn.q_proj => blk.10.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.10.self_attn.q_proj => blk.10.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.10.self_attn.v_proj => blk.10.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.10.self_attn.v_proj => blk.10.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.11.self_attn.k_proj => blk.11.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.11.self_attn.k_proj => blk.11.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.11.self_attn.o_proj => blk.11.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.11.self_attn.o_proj => blk.11.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.11.self_attn.q_proj => blk.11.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.11.self_attn.q_proj => blk.11.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.11.self_attn.v_proj => blk.11.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.11.self_attn.v_proj => blk.11.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.12.self_attn.k_proj => blk.12.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.12.self_attn.k_proj => blk.12.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.12.self_attn.o_proj => blk.12.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.12.self_attn.o_proj => blk.12.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.12.self_attn.q_proj => blk.12.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.12.self_attn.q_proj => blk.12.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.12.self_attn.v_proj => blk.12.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.12.self_attn.v_proj => blk.12.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.13.self_attn.k_proj => blk.13.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.13.self_attn.k_proj => blk.13.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.13.self_attn.o_proj => blk.13.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.13.self_attn.o_proj => blk.13.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.13.self_attn.q_proj => blk.13.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.13.self_attn.q_proj => blk.13.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.13.self_attn.v_proj => blk.13.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.13.self_attn.v_proj => blk.13.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.14.self_attn.k_proj => blk.14.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.14.self_attn.k_proj => blk.14.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.14.self_attn.o_proj => blk.14.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.14.self_attn.o_proj => blk.14.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.14.self_attn.q_proj => blk.14.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.14.self_attn.q_proj => blk.14.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.14.self_attn.v_proj => blk.14.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.14.self_attn.v_proj => blk.14.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.15.self_attn.k_proj => blk.15.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.15.self_attn.k_proj => blk.15.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.15.self_attn.o_proj => blk.15.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.15.self_attn.o_proj => blk.15.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.15.self_attn.q_proj => blk.15.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.15.self_attn.q_proj => blk.15.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.15.self_attn.v_proj => blk.15.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.15.self_attn.v_proj => blk.15.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.16.self_attn.k_proj => blk.16.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.16.self_attn.k_proj => blk.16.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.16.self_attn.o_proj => blk.16.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.16.self_attn.o_proj => blk.16.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.16.self_attn.q_proj => blk.16.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.16.self_attn.q_proj => blk.16.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.16.self_attn.v_proj => blk.16.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.16.self_attn.v_proj => blk.16.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.17.self_attn.k_proj => blk.17.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.17.self_attn.k_proj => blk.17.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.17.self_attn.o_proj => blk.17.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.17.self_attn.o_proj => blk.17.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.17.self_attn.q_proj => blk.17.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.17.self_attn.q_proj => blk.17.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.17.self_attn.v_proj => blk.17.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.17.self_attn.v_proj => blk.17.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.18.self_attn.k_proj => blk.18.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.18.self_attn.k_proj => blk.18.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.18.self_attn.o_proj => blk.18.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.18.self_attn.o_proj => blk.18.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.18.self_attn.q_proj => blk.18.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.18.self_attn.q_proj => blk.18.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.18.self_attn.v_proj => blk.18.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.18.self_attn.v_proj => blk.18.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.19.self_attn.k_proj => blk.19.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.19.self_attn.k_proj => blk.19.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.19.self_attn.o_proj => blk.19.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.19.self_attn.o_proj => blk.19.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.19.self_attn.q_proj => blk.19.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.19.self_attn.q_proj => blk.19.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.19.self_attn.v_proj => blk.19.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.19.self_attn.v_proj => blk.19.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.2.self_attn.k_proj => blk.2.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.2.self_attn.k_proj => blk.2.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.2.self_attn.o_proj => blk.2.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.2.self_attn.o_proj => blk.2.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.2.self_attn.q_proj => blk.2.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.2.self_attn.q_proj => blk.2.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.2.self_attn.v_proj => blk.2.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.2.self_attn.v_proj => blk.2.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.20.self_attn.k_proj => blk.20.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.20.self_attn.k_proj => blk.20.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.20.self_attn.o_proj => blk.20.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.20.self_attn.o_proj => blk.20.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.20.self_attn.q_proj => blk.20.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.20.self_attn.q_proj => blk.20.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.20.self_attn.v_proj => blk.20.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.20.self_attn.v_proj => blk.20.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.21.self_attn.k_proj => blk.21.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.21.self_attn.k_proj => blk.21.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.21.self_attn.o_proj => blk.21.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.21.self_attn.o_proj => blk.21.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.21.self_attn.q_proj => blk.21.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.21.self_attn.q_proj => blk.21.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.21.self_attn.v_proj => blk.21.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.21.self_attn.v_proj => blk.21.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.22.self_attn.k_proj => blk.22.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.22.self_attn.k_proj => blk.22.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.22.self_attn.o_proj => blk.22.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.22.self_attn.o_proj => blk.22.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.22.self_attn.q_proj => blk.22.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.22.self_attn.q_proj => blk.22.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.22.self_attn.v_proj => blk.22.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.22.self_attn.v_proj => blk.22.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.23.self_attn.k_proj => blk.23.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.23.self_attn.k_proj => blk.23.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.23.self_attn.o_proj => blk.23.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.23.self_attn.o_proj => blk.23.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.23.self_attn.q_proj => blk.23.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.23.self_attn.q_proj => blk.23.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.23.self_attn.v_proj => blk.23.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.23.self_attn.v_proj => blk.23.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.24.self_attn.k_proj => blk.24.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.24.self_attn.k_proj => blk.24.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.24.self_attn.o_proj => blk.24.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.24.self_attn.o_proj => blk.24.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.24.self_attn.q_proj => blk.24.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.24.self_attn.q_proj => blk.24.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.24.self_attn.v_proj => blk.24.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.24.self_attn.v_proj => blk.24.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.25.self_attn.k_proj => blk.25.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.25.self_attn.k_proj => blk.25.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.25.self_attn.o_proj => blk.25.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.25.self_attn.o_proj => blk.25.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.25.self_attn.q_proj => blk.25.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.25.self_attn.q_proj => blk.25.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.25.self_attn.v_proj => blk.25.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.25.self_attn.v_proj => blk.25.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.26.self_attn.k_proj => blk.26.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.26.self_attn.k_proj => blk.26.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.26.self_attn.o_proj => blk.26.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.26.self_attn.o_proj => blk.26.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.26.self_attn.q_proj => blk.26.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.26.self_attn.q_proj => blk.26.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.26.self_attn.v_proj => blk.26.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.26.self_attn.v_proj => blk.26.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.27.self_attn.k_proj => blk.27.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.27.self_attn.k_proj => blk.27.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.27.self_attn.o_proj => blk.27.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.27.self_attn.o_proj => blk.27.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.27.self_attn.q_proj => blk.27.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.27.self_attn.q_proj => blk.27.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.27.self_attn.v_proj => blk.27.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.27.self_attn.v_proj => blk.27.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.28.self_attn.k_proj => blk.28.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.28.self_attn.k_proj => blk.28.attn_k.weight.loraB (5120, 16) float32 0.31MB
model.layers.28.self_attn.o_proj => blk.28.attn_output.weight.loraA (5120, 16) float32 0.31MB
model.layers.28.self_attn.o_proj => blk.28.attn_output.weight.loraB (5120, 16) float32 0.31MB
model.layers.28.self_attn.q_proj => blk.28.attn_q.weight.loraA (5120, 16) float32 0.31MB
model.layers.28.self_attn.q_proj => blk.28.attn_q.weight.loraB (5120, 16) float32 0.31MB
model.layers.28.self_attn.v_proj => blk.28.attn_v.weight.loraA (5120, 16) float32 0.31MB
model.layers.28.self_attn.v_proj => blk.28.attn_v.weight.loraB (5120, 16) float32 0.31MB
model.layers.29.self_attn.k_proj => blk.29.attn_k.weight.loraA (5120, 16) float32 0.31MB
model.layers.29.self_attn.k_proj => blk.29.attn_k.weight.loraB (5120, 16) float32 0.31MB
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Converted ./ming/adapter_config.json and ./ming/adapter_model.safetensors to ./ming/ggml-adapter-model.bin

后续需要将 ggml-adapter-model.bin 转换成 gguf 提示如下：

(ollama) ╭─hougelangley at Arch-Legion in ~/ollama on main✘✘✘ 24-04-17 - 22:40:01
╰─(ollama) ⠠⠵ python llm/llama.cpp/convert-llama-ggml-to-gguf.py -i ming/ggml-adapter-model.bin -o ming.bin
* Using config: Namespace(input=PosixPath('ming/ggml-adapter-model.bin'), output=PosixPath('ming.bin'), name=None, desc=None, gqa=1, eps='5.0e-06', context_length=2048, model_metadata_dir=None, vocab_dir=None, vocabtype='spm,hfft')

=== WARNING === Be aware that this conversion script is best-effort. Use a native GGUF model if possible. === WARNING ===

- Note: If converting LLaMA2, specifying "--eps 1e-5" is required. 70B models also need "--gqa 8".
* Scanning GGML input file
Traceback (most recent call last):
  File "/home/hougelangley/ollama/llm/llama.cpp/convert-llama-ggml-to-gguf.py", line 441, in <module>
    main()
  File "/home/hougelangley/ollama/llm/llama.cpp/convert-llama-ggml-to-gguf.py", line 415, in main
    offset = model.load(data, 0)  # noqa
             ^^^^^^^^^^^^^^^^^^^
  File "/home/hougelangley/ollama/llm/llama.cpp/convert-llama-ggml-to-gguf.py", line 175, in load
    offset += self.validate_header(data, offset)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/hougelangley/ollama/llm/llama.cpp/convert-llama-ggml-to-gguf.py", line 160, in validate_header
    raise ValueError(f"Unexpected file magic {magic!r}! This doesn't look like a GGML format file.")
ValueError: Unexpected file magic b'algg'! This doesn't look like a GGML format file.
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