Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Failed to execute script 'koboldcpp' due to unhandled exception! #180

Closed
valdesguefa opened this issue May 17, 2023 · 2 comments
Closed

Comments

@valdesguefa
Copy link

i have this issue when i try to run vicuna-13b model

Attempting to Load...

System Info: AVX = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | VSX = 0 |
llama.cpp: loading model from G:\AI_and_data\LLAMA_models\LLama_for_windows\ggml-vicuna-13b-4bit.bin
llama_model_load_internal: format = ggjt v1 (pre ggerganov#1405)
llama_model_load_internal: n_vocab = 32001
llama_model_load_internal: n_ctx = 2048
llama_model_load_internal: n_embd = 5120
llama_model_load_internal: n_mult = 256
llama_model_load_internal: n_head = 40
llama_model_load_internal: n_layer = 40
llama_model_load_internal: n_rot = 128
llama_model_load_internal: ftype = 2 (mostly Q4_0)
llama_model_load_internal: n_ff = 13824
llama_model_load_internal: n_parts = 1
llama_model_load_internal: model size = 13B

Legacy LLAMA GGJT compatability changes triggered.
llama_model_load_internal: ggml ctx size = 90.75 KB
llama_model_load_internal: mem required = 9807.49 MB (+ 1608.00 MB per state)
Traceback (most recent call last):
File "koboldcpp.py", line 648, in
File "koboldcpp.py", line 578, in main
File "koboldcpp.py", line 161, in load_model
OSError: [WinError -1073741795] Windows Error 0xc000001d
[340] Failed to execute script 'koboldcpp' due to unhandled exception!

@LostRuins
Copy link
Owner

Try running it with --noavx2

@LostRuins
Copy link
Owner

If you're still interested in trying it, you can run it with --noblas --noavx2 --nommap with the latest version. That will trigger failsafe mode that should have the widest compatibility.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants