Expected Behavior
This happens (so far) only with these models:
Wizard-Vicuna-30B-Uncensored.ggmlv3.q8_0.bin
WizardLM-30B-Uncensored.ggmlv3.q8_0.bin
based-30b.ggmlv3.q8_0.bin
Larger 65B models work fine. It could be something related to how these models are made, I will also reach out to @ehartford
llama-cpp-python 0.1.59 installed with OpenBLAS
CMAKE_ARGS="-DLLAMA_OPENBLAS=on" FORCE_CMAKE=1 pip install llama-cpp-python --force-reinstall --upgrade --no-cache-dir
I was running my usual code on the CPU and restarting it to tweak the results when this error came up. I made no code changes, only to context length, I reduced it as it was exceeding the 2048 token limit.
processed_output = self.llm(
context + "\n### Instruction: \n" + instruction + "\n### Input: \n" + input_text + output,
max_tokens=400,
stop=None,
temperature=0.7,
repeat_penalty=1.1,
top_k=80,
top_p=0.5,
echo=True,
)
Current Behavior
llama.cpp: loading model from /home/****/models/Wizard-Vicuna-30B-Uncensored-GGML/Wizard-Vicuna-30B-Uncensored.ggmlv3.q8_0.bin
llama_model_load_internal: format = ggjt v3 (latest)
llama_model_load_internal: n_vocab = 32000
llama_model_load_internal: n_ctx = 2048
llama_model_load_internal: n_embd = 6656
llama_model_load_internal: n_mult = 256
llama_model_load_internal: n_head = 52
llama_model_load_internal: n_layer = 60
llama_model_load_internal: n_rot = 128
llama_model_load_internal: ftype = 7 (mostly Q8_0)
llama_model_load_internal: n_ff = 17920
llama_model_load_internal: n_parts = 1
llama_model_load_internal: model size = 30B
llama_model_load_internal: ggml ctx size = 0.13 MB
llama_model_load_internal: mem required = 35267.28 MB (+ 6248.00 MB per state)
.
llama_init_from_file: kv self size = 6240.00 MB
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 = 0 | SSE3 = 1 | VSX = 0 |
Processing all summaries...
ggml_new_tensor_impl: not enough space in the scratch memory pool (needed 546644800, available 536870912)
Segmentation fault
Environment and Context
wsl2
python 3.10.9
- Physical (or virtual) hardware you are using, e.g. for Linux:
$ lscpu
AMD Ryzen 9 3900XT 12-Core Processor
- Operating System, e.g. for Linux:
$ uname -a
5.15.68.1-microsoft-standard-WSL2+ #2 SMP
$ python3 3.10.9
$ make GNU Make 4.3
$ g++(Ubuntu 11.3.0-1ubuntu1~22.04.1) 11.3.0
To me it is 100% reproducible after several inference runs with Wizard-Vicuna-30B-Uncensored.ggmlv3.q8_0.bin
Expected Behavior
This happens (so far) only with these models:
Wizard-Vicuna-30B-Uncensored.ggmlv3.q8_0.bin
WizardLM-30B-Uncensored.ggmlv3.q8_0.bin
based-30b.ggmlv3.q8_0.bin
Larger 65B models work fine. It could be something related to how these models are made, I will also reach out to @ehartford
llama-cpp-python 0.1.59 installed with OpenBLAS
CMAKE_ARGS="-DLLAMA_OPENBLAS=on" FORCE_CMAKE=1 pip install llama-cpp-python --force-reinstall --upgrade --no-cache-dir
I was running my usual code on the CPU and restarting it to tweak the results when this error came up. I made no code changes, only to context length, I reduced it as it was exceeding the 2048 token limit.
Current Behavior
Environment and Context
wsl2
python 3.10.9
$ lscpuAMD Ryzen 9 3900XT 12-Core Processor
$ uname -a5.15.68.1-microsoft-standard-WSL2+ #2 SMP
To me it is 100% reproducible after several inference runs with Wizard-Vicuna-30B-Uncensored.ggmlv3.q8_0.bin