Llama cpp python gpu github

Llama cpp python gpu github. cpp's . The best solution would be to delete all VS and CUDA. For more detailed examples leveraging Hugging Face, see llama-recipes. pseudotensor changed the title 0. The demo script below uses this. cpp commit, also compiled against CUDA 12. May 13, 2023 · When you build llama. Current Behavior. also has no effect. Learn more in the documentation. python -m pip install . I have found the reason for the slow inference speed. Then overwrite the old . In generell the gpu offloading works on my system (sentence-transformers runs perfectly on gpu) only llama-cpp is giving me trouble. I am running python 3. Something like that. I took a look at llama_cpp. I am able to sucesfully run 4 llama2-7B models on this system. llama cpp python no longer uses GPU abetlen Apr 4, 2024 · On Latest version 0. 59) to install via standard pip albeit without Metal GPU support. dll file too. After it processes the prompt, it will continue text generation without BLAS since the overhead in this case is too big and there is no benefit". In addition, when all 2 GPUs are visible, tensor_split option doesnt work as expected, since nvidia-smi shows, that both GPUs are used. generate: prefix-match hit. 58 ms / 8 tokens ( 455. I built a RAG Q&A pipeline using LlamaIndex and Llama-cpp-python in the past. ARM64 or x86_64 (and then within x86_64 it may (or may not) use F16C, AVX, AVX2 and This allows you to use llama. make clean; make LLAMA_OPENBLAS=1; Next time you run llama. Hereafter, I will paste relevant snippets of code with the memory and Apr 27, 2024 · Issues I am trying to install the lastest version of llama-cpp-python in my windows 11 with RTX-3090ti(24G). LLAMA_SPLIT_* for options. Modify Makefile to point to the lib . A GPT4All model is a 3GB - 8GB file that you can download and plug into the GPT4All software. import torch. 7B params with a 3080TI: llama_print_timings: prompt eval time = 695. model quantization, changes to CMake builds, improved CUDA support, CUBLAST support, etc. 1. And main_gpu also tried 0,1,2. /server [options] options:-h, --help show this help message and exit-v, --verbose verbose output (default: disabled)-t N, --threads N number of threads to use during computation (default: 48)-tb N, --threads-batch N number of threads to use during batch and prompt processing (default: same as --threads)-c N, --ctx-size N size of the prompt context (default: 512)--rope-scaling {none More than 100 million people use GitHub to discover, fork, and contribute to over 330 million projects. 58 Jun 7, 2023 · I can, however, get llama-cpp-python (v0. GPT4All is an ecosystem to run powerful and customized large language models that work locally on consumer grade CPUs and NVIDIA and AMD GPUs. 2x A100 GPU server, cuda 12. Physical (or virtual) hardware you are using, e. llama_speculative import LlamaPromptLookupDecoding llama = Llama ( model_path = "path/to/model. server --model models/codellama-13b-instruct. Apr 26, 2024 · llama_cpp_python 0. LlamaInference - this one is a high level interface that tries to take care of most things for you. gjmulder changed the title Set gpu device Set GPU device on multi-GPU systems on May 30, 2023. --no_offload_kqv: Do not offload the K, Q, V to the GPU. LLAMA_CTX_SIZE: The context size to use (default is 2048) LLAMA_MODEL: The name of the model to use (default is /models/llama-2-13b-chat. server --model <model_path> --n_ctx 16192. May 30, 2023 · First I would like to share my great appreciation for this library 👏👏👏 Trying to run on GPU (+CPU but I don't know the limits yet) The script: from llama_cpp import Llama llm = Llama(model_path=". Similar to Hardware Acceleration section above, you can also install with Mar 13, 2024 · version llama-cpp-python-0. When runing the complie instructions from #182, CMake's find_package() instruction will not look at the correct location where my CUADToolkit is installed. API. 04 - X86 CUDA: 11. thank you! Is there an existing issue for this? I have searched the May 30, 2023 · There's an open bug upstream with llama. Environment and Context Mar 30, 2023 · cd llama. I tried a lot of things to install llama-cpp-python for GPU as written in readme, but when I execute the code it's always I have used shorter context length as well, but it is not working. You signed out in another tab or window. When I try inference on tinyllama using llama-cpp-python it doesn't utilize the Tesla gpu on the machine. To install the server package and get started: pip install llama-cpp-python[server] python3 -m llama_cpp. --logits_all: Needs to be set for perplexity evaluation to work. Apr 13, 2024 · You signed in with another tab or window. e. This llama. cpp had a total execution time that was almost 9 seconds faster than llama-cpp-python (about 28% faster). May 29, 2023 · gjmulder added the hardware label on May 30, 2023. Assets 19. When I made the switch, I noticed a significant increase in response time. Note that your CPU needs to support AVX instructions. cpp (e. OS: Ubuntu 22. With a 7B model and an 8K context I can fit all the layers on the GPU in 6GB of VRAM. Oct 26, 2023 · Hi guys, I have a windows 11 with a GPU NVIDIA GeForce RTX 4050. gz (37. I tried manually installing the llama-cpp-python with the llama. May 12, 2023 · If CuBLAS is enabled it with use CuBLAS. Run llama. cpp, while it started at around 80% and gradually dropped to below 60% for llama-cpp-python, which might be indicative of the performance discrepancy. Please tell me what else I have missed or what environment I am missing. n_threads, n_parts and n May 2, 2023 · In your case, you need to pass a prompt with length of 32 or more tokens to main to make it use BLAS. This seems to occur once the prompt is sufficiently long, with small models getting maybe a hundred tokens worth of dialogue, and larger models falling over almost immediately. pip install llama-cpp-python --upgrade --force-reinstall --no-cache-dir --verbose. 84 --force-reinstall --upgrade --no-cache-dir --verbose !pip install -q huggingface_hub. thanks Nov 15, 2023 · With both installed, never uses GPU, no mention of offlload as usual, etc. ImportError: cannot import name 'Llama' from partially initialized module 'llama_cpp' (most likely due to a circular import) (c:\Projects\LangChainPythonTest\david\llama_cpp. I'm also having issues with latest version, 0. 11, 2. I have succesfully followed all the instructions, tips, suggestions, recomendations on the instruction documents to run the privateGPU locally with GPU. cppは実はpythonでも使える。. cpp API. metal next to the pytohn executable etc etc etc. urlretrieve ( file_link, filename ) Apr 22, 2024 · rm -rf _skbuild/ # delete any old builds. 5 MB) 5 days ago · this is how i run llama. gguf -c 8192 -ngl 100 --timeout 10. If the model is too big to fit on VRAM, i'd expect an exception to be raised, that i could catch to proceed accordingly. Collecting llama-cpp-python Downloading llama_cpp_python-0. qa_with_sources import load_qa_with_sources_chain n_gpu_layers = 4 # Change this value based on your model and your GPU VRAM pool. The command pip uninstall -y llama-cpp-python CMAKE_ARGS="-DLLAMA_CUBLAS=on" FORCE_CMAKE=1 pip install l Python bindings for llama. - ollama/ollama Aug 26, 2023 · Owner. I need your help. cpp given through the PR here, both including and not including the --tensor-split arg but resulted in segmentation fault while loading model. /server -t 8 -a llama-3-8b-instruct -m . gguf", draft_model = LlamaPromptLookupDecoding (num_pred_tokens = 10) # num_pred_tokens is the number of tokens to predict 10 is the default and generally good for gpu, 2 performs better for cpu-only machines. cpp yesterday merge multi gpu branch, which help us using small VRAM GPUS to deploy LLM. 29 or higher I experience a significant (>50%) loss of performance in the number of tokens generated per second for my example code below. Then just update your settings in . See llama_cpp. Performance is right in between nvidia's cuBLAS (using all GPU layers) and openBLAS/ cuBLAS` without GPU support. 87 (can't exactly remember) months ago while using: set FORCE_CMAKE=1 set CMA Jun 22, 2023 · Describe the bug I install by One-click installers. 59, there's a segfault on at least an AMD RX7900XT when using models loaded with the llama. Proprietary Nvidia Vulkan with GPU: 22 tokens/sec. py I get: Loading model: Meta-Llama-3-8B-Instruct. cpp's instructions to cmake llama. pytorch vers Dec 18, 2023 · The model is initialized with main_gpu=0, tensor_split=None. One way to do this is to build from source llama-cpp-python and then: Mar 9, 2016 · conda create -n llama python=3. If it's True then you have the right ROCm and Pytorch installed and things should work. Downgrading llama-cpp-python to version 0. If this fails, add --verbose to the pip install see the full cmake build log. this is how i run llama-cpp-python which results in a response time of 18 seconds for my bot I'm trying llama-cpp-python (v0. 13B llama model cannot fit in a single 3090 unless using quantization. cpp loader. Increment ngl=NN until you are using almost all your VRAM. Also when running the model through llama cp python, it says the layer count on load of the model: llama_model_load_internal: n_layer = 40. cpp. Also other parameters like n_ctx and n_batch can cause a crash. 64 use llm model: Phi-3-mini-4k-instruct-q4. I'll try WSL next and failing that, Docker. But the long and short of it is that there are two interfaces. It works properly while installing llama-cpp-python on interactive mode but not inside the dockerfile. One thing I found is the params printed on the console are different when using llama. 16, tried ggml-metal. ), so it is best to revert to the exact llama. This will also build llama. 18 (and others?) no longer use GPU properly. At least for Stable diffusion that's how you check and make it work. gguf --n_gpu_layers 45 Mar 23, 2023 · To install the package, run: pip install llama-cpp-python. dll with the new one and add the clblast. abetlencommented Aug 27, 2023. I'm using a virtual environment through Anaconda3. 18) with Nvidia GPUs. 「llama-cpp-python+cuBLASでGPU推論さ Apr 30, 2023 · In comparison when I run the same llama. * make tests explicitly send temperature to OAI API. You switched accounts on another tab or window. Download model from HF There are two AMDW6800 graphics cards on the current machine. so file in the LDFLAGS variable. Wheel builds but when running it doesn't seem to be using CUDA (0% GPU). I have used these command for pip install: !CMAKE_ARGS="-DLLAMA_CUBLAS=on" FORCE_CMAKE=1 pip install llama-cpp-python==0. gguf: embedding length = 4096. llama_print_timings: sample time = 30. Make sure your VS tools are those CUDA integrated to during install. cpp propagates to llama-cpp-python in time. Please advise. Otherwise, ignore it, as it makes prompt processing slower. cpp which with the latest update results in a response time of 3 seconds for my bot. cpp about it not cleaning up GPU VRAM. cpp, so if you are compiling from source on a newer commit, you will hit this issue. isfile ( filename ): urllib. Llama(), the memory of the 4 GPUs are evenly distributed. I have a system with 4 CUDA enabled GPUs, each with 16GB of VRAM. Second run, I try the low_level python wrapper around the same llama. 18 (and others?) no longer use GPU at all on Nov 15, 2023. Sep 20, 2023 · I want llama-cpp-python to be able to load GGUF models with GPU inside docker. 1 via llama-cpp-python: llama_print_timings: load time = 3646. Looks like right after llm = llama_cpp. LlamaContext - this is a low level interface to the underlying llama. set_cache. I observe that the clip model forces CPU backend, while the llm part uses CUDA. LLM inference in C/C++. request from llama_cpp import Llama def download_file ( file_link, filename ): # Checks if the file already exists before downloading if not os. chains. So this code in llama-cpp-python is now invalid when paired with llama. 56, how to enable CLIP offload to GPU? the llama part is fine, but CLIP is too slow my 3090 can do 50 token/s but total time would be tooo slow(92s), much slower than my Macbook M3 max(6s), i'v tried: CMAKE_ARGS="-DLLAMA_CUBLAS=on -DLLAVA_BUILD=on" pip install llama-cpp-python but it does not work Apr 3, 2024 · Saved searches Use saved searches to filter your results more quickly Feb 26, 2024 · hockeybro12 commented on Feb 27. Apr 29, 2024 · Hi, I am trying to get llama-cpp-python with GPU Support on Windows 11 Azure VM. 29 ms / 150 tokens ( 4. 19 with cuBLAS backend Aug 7, 2023 · usually a 13B model based on Llama have 40 layers. A simple example that uses the Zephyr-7B-β LLM for text generation: import os import urllib. Jul 5, 2023 · git clone llama-cpp-python from source and checkout v0. First attempt at full Metal-based LLaMA inference: llama : Metal inference #1642. --cache-capacity CACHE_CAPACITY: Maximum cache capacity (llama-cpp-python). Jun 21, 2023 · There's continuous change in llama. Contribute to ggerganov/llama. Finally the GPU will likely only be active if your prompts are longer than 32. gguf: This GGUF file is for Little Endian only. Environment and Context. txt usage: . /vendor/llama. Documentation is TBD. Follow llama. $ docker pull ghcr. 65 and below crashes (memory issue?) and v0. Nov 7, 2023 · The same issue has been resolved in llama. path. gjmulder closed this as completed on May 30, 2023. Activate NUMA task allocation for llama. Proprietary Nvidia cuBLAS without -ngl 99: May 16, 2023 · The n_parts argument got removed from a recent version of llama. llama. I had a new conda env, with python 3. I'm not familiar with C++ so I might be missing something obvious. cpp version (downloaded into /vendor dir), on the same machine: Apr 12, 2023 · MNIST prototype of the idea above: ggml : cgraph export/import/eval example + GPU support ggml#108. cpp && git pull -r origin master; install llama-cpp-python from local source: pip install /path/to/llama-cpp-python About GPT4All. 2. ) UI or CLI with streaming of all models Upload and View documents through the UI (control multiple collaborative or personal collections) May 19, 2023 · CMAKE_ARGS="-DLLAMA_CUBLAS=on" FORCE_CMAKE=1 pip install llama-cpp-python Ensure you install the correct version of CUDA toolkit When I installed with cuBLAS support and tried to run, I would get this error b2865. /Meta-Llama-3-8B-Instruct-Q6_K. I have successfully installed llama-cpp-python=0. If you have a bigger model, it should be possible to just google the number of layers for this specific, or general models with the same parameter count. これの良いところはpythonアプリに組み込むときに使える点。. Even if I tried changing n_gpu_layers to -1,0, or other values. GPU no working. On Windows, I can use these commands in CMD: set FORCE_CMAKE= Apr 20, 2024 · CMAKE_ARGS="-DLLAMA_CUDA=on" pip install llama-cpp-python This should be installing in colab environment. Jan 31, 2024 · はじめに. 33 works fine. I have a single api which loads the models into a pool and uses a queue system to process queries in a first in first out sequence. cpp cli vs llama-cpp-python. cpp documentation for the complete list of server options. Aug 7, 2023 · To check if you have CUDA support via ROCm, do the following : $ python. vscode/settings. Proprietary Nvidia drivers: cuBLAS with all graphics layers ( -ngl 99 ): 33 tokens/sec. 62 (you needed xcode installed in order pip to build/compile the C++ code) Mar 10, 2010 · I'm not sure if this is supposed to work on Windows or not so maybe that's the issue. Set model parameters. 51 ms / 50 runs ( 0. This is the pattern that we should follow and try to apply to LLM inference. py) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "C:\Projects from llama_cpp import Llama from llama_cpp. . But you could ask the lllama_cpp_python Apr 19, 2023 · Okay, i spent several hours trying to make it work. python3 -m llama_cpp. 64 ms per token) Use the cache: llama_cpp. cp This release includes model weights and starting code for pre-trained and fine-tuned Llama language models — ranging from 7B to 70B parameters. Llama. I downloaded the llama. I have 4 T4 GPUs to load a large size model which does not fit in one T4. gguf: context length = 8192. gguf. LLAMA_SPLIT_LAYER: ignored. GPUオフロードにも対応しているのでcuBLASを使ってGPU推論できる。. cpp development by creating an account on GitHub. 1, evaluated llama-cpp-python versions: 2. 63. pseudotensor added a commit to h2oai/h2ogpt that referenced this issue on Nov 15, 2023. similarity_search(query) from langchain. main_gpu ( int, default: 0 ) –. More details in #223. ccp interrogating the hardware it is being compiled on and then aggressively optimising its compiled code to perform for that specific hardware (e. for Linux: Intel(R) Core(TM) i7-8700K CPU @ 3. Jun 14, 2023 · I'm trying to let a user select and load a large model on GPU using cuBLAS. 16 conda activate llama (4) Install the LATEST llama-cpp-pythonwhich happily supports MacOS Metal GPU as of version 0. torch. Aug 2, 2023 · Use a faster GPU or a smaller model. json to point to your code completion server: Jul 13, 2023 · llama-cpp-python-0. Similarly, the 13B model will fit in 11GB of VRAM: llama_model_load_internal: format = ggjt v3 (latest) llama_model_load_internal: n Dec 18, 2023 · The package has been installed using the following parameters: CMAKE_ARGS= "-DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS" python -m pip install llama-cpp-python. AFAIK, the Python garbage collector should clean-up a model object that resides in CPU RAM when there's no references to it. cpp commit your llama-cpp-python is using and verify that that compiles and runs with no issues. This saves VRAM but reduces the performance. Answered: How use GGUF model on h2oGPT for CPU h2oai/h2ogpt#904. If you can, log an issue with llama. then I run it, just CPU work. 61 ms per run) llama_print_timings: prompt eval time = 3646. I have following code for model inference: model_name_or_path May 19, 2023 · As per @jmtatsch's reply to my idea of pushing pre-compiled Docker images to Docker hub, providing precompiled wheels is likely equally problematic due to:. 9. cd . GPU utilization was constant at around 93% for llama. cpp; Modify Makefile to point to the include path, -I, in the CFLAGS variable. Apr 5, 2024 · Since the update to llama_cpp_python / llama_cpp_python_cuda 0. From: Apr 8, 2023 · Model loading (until first input shows): ~ 6 seconds. io/ abetlen / llama-cpp-python: Nov 25, 2023 · You signed in with another tab or window. EX: F:\privateGPT>set LLAMA_CUBLAS=1 && set FORCE_CMAKE=1 && pip install llama-cpp-python. 8 (in miniconda) llama-cpp-python: 0. /main with the same arguments you previously passed to llama-cpp-python and see if you can reproduce the issue. ggerganov/llama. tar. cpp, and GPT4ALL models; Attention Sinks for arbitrarily long generation (LLaMa-2, Mistral, MPT, Pythia, Falcon, etc. llama. cpp GGML models, and CPU support using HF, LLaMa. You can use this similar to how the main Sep 15, 2023 · Hi everyone ! I have spent a lot of time trying to install llama-cpp-python with GPU support. cpp directory directly, and copied over the new dll's, but now my software doesn't recognize the model anymore. 28 to 0. That leaves current llama-cpp-python cuBLAS support at these models: LLAMA BAICHUAN FALCON May 15, 2023 · Hello, just following up on this issue in case others were wondering about the same thing. 10, latest cuda drivers and tried different llama-cpp verisons. After first instruction, response shows after: ~7 seconds. py reference, which includes a n_gpu_layers argument in the llama_context_params structure, but I cannot figure out how to actually pass that value; I can't see anywhere it is actually modified. Note BLAS param in the output. set FORCE_CMAKE=1. cpp commit removes the n_parts parameter: ggerganov/llama. 0. 一方で環境変数の問題やpoetryとの相性の悪さがある。. Apr 18, 2023 · from llama_cpp import Llama. Jul 31, 2023 · It's being resolved in codestar model,as I understand, but not in Llama-cpp-python. n_batch = 512 # Should be between 1 and n_ctx, consider the amount of VRAM in your GPU. Jan 23, 2024 · The performance of my example code below should stay the same for different versions of llama-cpp-python. I'm now limited to 500 tokens, and that is far from enough and from the reason why I developed a model myself. Jul 20, 2023 · Have the same issue, llama. 8 Python: 3. g. / GPU support from HF and LLaMa. I do not see the library files here Apr 4, 2024 · But if I try more complex prompts the model crashes with: Llama. 70 errors out with GPU #477 jaymon0703 opened this issue Jul 14, 2023 · 2 comments Labels May 23, 2023 · Run without the ngl parameter and see how much free VRAM you have. 64 ms. Jun 20, 2023 · I recently discovered that llama-cpp-python can be compiled with cuBLAS support for all supported GPU architectures by setting the CUDAFLAGS environment variable to -arch=all. I'll keep monitoring the thread and if I need to try other options and provide info post and I'll send everything quickly. Hey guys, what i'm doing wrong here it's a windows 11 machine, rtx 3050. . 13, 2. gguf: feed forward length = 14336. EDIT: In other words my test prompts were too short for the GPU to be used. Get up and running with Llama 3, Mistral, Gemma, and other large language models. LLAMA_SPLIT_ROW: the GPU that is used for small tensors and intermediate results. server --model models/7B/llama-model. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. So few ideas. Pre-built Wheel (New) It is also possible to install a pre-built wheel with basic CPU support. question_answering import load_qa_chain from langchain. Dec 4, 2023 · Saved searches Use saved searches to filter your results more quickly Oct 2, 2023 · WaleedAlfaris. 79 (pip install llama-cpp-python==0. This all only happens when I use the GPU. Since I work in a hospital my aim is to be able to do it offline (using the downloaded tar. After second instruction, response shows after: ~4 seconds. cpp, but don't know if llama. pseudotensor mentioned this issue on Oct 6, 2023. app-1 exited with code 139. Jun 26, 2023 · Describe the bug llama-cpp-python with GPU accelleration has issues building with a system that has gcc that is too recent (gcc 12). You need to set n_gpu_layers=1000 when you create the model to get full GPU offloading, assuming you have enough VRAM for the model size you are using. gguf) LLAMA_N_GPU_LAYERS: The number of layers to run on the GPU (default is 99) See the llama. @edzakharyan97this is due to the recent update to GGUF (check the README) older model viles (ggmlv3) are no longer supported from v0. I am using Llama () function for chatbot in terminal but when i set n_gpu_layers=-1 or any other number it doesn't engage in computation. Would you know what might cause this slowdown? Jan 29, 2024 · Vulkan recognizes the proprietary Nvidia driver. change default temperature of OAI compat API from 0 to 1 (#7226) * change default temperature of OAI compat API from 0 to 1. Reload to refresh your session. 78 should still work) you can upgrade old version files using the script linked from the README or just download the new GGUF format Jun 19, 2023 · docs = db. cpp with latest code: cd vendor/llama. cpp compatible models with any OpenAI compatible client (language libraries, services, etc). To install the package, run: pip install llama-cpp-python. In comparison when i set it on Lm Studio it works perfectly and fast I want the same thing but in te 问题5：回复内容很短 问题6：Windows下，模型无法理解中文、生成速度很慢等问题 问题7：Chinese-LLaMA 13B模型没法用llama. cpp you'll have BLAS turned on. cpp works with GPU but llama-cpp-python doesn't. Jun 8, 2023 · Multi-GPU inference is essential for small VRAM GPU. Run nvidia-smi to see if it is running a process on your GPU. It worked up untill yesterday but now it is failing to install. 66-0. is_available () Output : True or False. 65; update submodule of llama. cpp on Windows with CMake you can give it the option -DBUILD_SHARED_LIBS=ON and this file will be built, if you add -DLLAMA_CLBLAST=ON then it will build this file with CLBlast support. This repository is intended as a minimal example to load Llama 2 models and run inference. cpp mainline: llama-cpp-python/llama_cpp Then you'll need to run the OpenAI compatible web server with a increased context size substantially for GitHub Copilot requests: python3 -m llama_cpp. The model runs correctly, but it always sticks to the CPU even when setting n_gpu_layers=-1 as seen in the docs. However, When I do this, the models are split accross the 4 GPUs Oct 11, 2023 · The REFACT and MPT entries are new model arch support that isn't present yet in the current version of llama-cpp-python. How to split the model across GPUs. Python bindings for llama. 55 fixes this issue. Than the only solution seems to reduce the param n_gpu_layers from a value of 30 to only 10. request. Contribute to abetlen/llama-cpp-python development by creating an account on GitHub. main_gpu interpretation depends on split_mode: LLAMA_SPLIT_NONE: the GPU that is used for the entire model. Q5_K_M. how to set? use my GPU to work. cpp@ dc271c5. gz file of llama-cpp-python). I want to switch from llama-cpp to ollama because ollama is more stable and easier to install. 82 ms per token) Python bindings for llama. 58 of llama-cpp-python. cpp启动，提示维度不一致 问题8：Chinese-Alpaca-Plus效果很差 问题9：模型在NLU类任务（文本分类等）上效果不好 问题10：为什么叫33B，不应该是30B吗？ Dec 31, 2023 · abetlen / llama-cpp-python Public. cpp from source and install it alongside this python package. cuda. 70GHz Apr 18, 2024 · When trying to convert from HF/safetensors to GGUF using convert-hf-to-gguf. Below are the details. When I update my llama-cpp-python dependency from 0. iz oy um ot yk jx nz vo qp rh