Kobold ai gpu reddit. 32 GiB already allocated; 0 bytes free; 5.
- Kobold ai gpu reddit When asking a question or stating a problem, please add as much detail as possible. amd has finally come out and said they are going to add rocm support for windows and consumer cards. Top. If you load the model up in Koboldcpp from the command line, you can see how many layers the model has, and how much memory is needed for each layer. There is a large open source model called BLOOM (176b) though. Go to the "files" part of the page, and download the q4_k_m . I'm mainly interested in Kobold AI, and maybe some Stable Diffusion on the side. I think it would load pretty slow, but in terms of inference, I'm not sure. There still is no ROCm driver, but we now have Vulkan support for that GPU available in the product I linked which will perform well on that GPU. The Pascal series (P100, P40, P10 ect) is the GTX 10XX series GPUs. If you want to run the full model with ROCM, you would need a different client and running on Linux, it seems. I also get the Kobold AI model erroring out for memory (in the 13B models) as well if I set the settings to high (I used to be This post discusses multi-GPU using Stable Diffusion, and while in the case of SD they're running multiple instances, not one shared instance, which is different than what Kobold is doing, it isn't clear to me that PCIe at 1x would significantly starve the GPU cores. I usually leave 1-2gb free to be on the They don't no, at least not officially and getting that working isn't worth it. The "Max Tokens" setting I can run is currently 1300-ish, before Kobold/Tavern runs out of memory, which I believe is using my ram(16GBs), so lets just assume that. I have 32GB RAM, Ryzen 5800x CPU, and 6700 XT GPU. I bought a HD to install Linux as a secondary OS just for that, but currently I've been using Faraday. 6 GB after a single back and forth The Q4/Q5 etc. GPU layers I've set as 14. I have a ryzen 5 5500 with an RX 7600 8gb Vram and 16gb of RAM. The only things I had opened at the time were the kobold tab and app and janitor ai. Reply reply /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and It's not really a calculation. ive downloaded, deleted and redownloaded Kobold multiple times, turned off my antivirus, and followed every instruction, however when i try and run the "play" batch file, it'll say "GPU support not found" is there way i can get my GPU working so i dont have to allocate all layers to my CPU? Well I don't know if I can post the link here, more after my disappointment when using the normal version of koboltAI (due to excessive GPU spending leaving me stuck with "weak" models). , it's using GPU for analysis, but not for generating output. Or check it out in the app stores TOPICS Well tavern ai is just a front end UI which takes the local port of kobold ai, good work still, I can now finally buy a intel arc as my next gpu I'll update this post to see how long I can use this wonderful AI. Very little data goes in or out of the gpu after a model is loaded (just your text and the AI output token rankings, which is measured in megabytes). I knowthat best solution Will be running kobold on Linux WITH AMD GPU, but i must run on Mac. By splitting layers, you can move some of the memory requirements around. 59 GiB reserved in total by PyTorch) I take it from the message this is a VRAM issue. I've already tried forcing KoboldAI to use torch-directml, as that supposedly can run on the GPU, but no success, as I probably don't understand enough about it. But the 2. New. One small issue I have with is trying to figure out how to run "TehVenom/Pygmalion-7b-Merged-Safetensors". Even at $. 7B-Horni, but it turns out that these are very powerful for what my pc is, I have an RTX GPU: GTX 1050 (up to 4gb VRAM) RAM: 8GB/16GB. Open comment sort options Are you trying to run locally with an NVIDIA graphics card, or CPU only (very slow) or using Horde? We're now read-only indefinitely due to Reddit Incorporated's poor management and decisions related to The context is put in the first available GPU, the model is split evenly across everything you select. You'll have the best results with PCIE 4. Welcome to KoboldAI on Google Colab, GPU Edition! KoboldAI is a powerful and easy way to use a variety of AI based text generation experiences. So it's not done in parallel, either. downloaded the latest update of kobold and it doesn't show my CPU at all. Open comment sort options. This is a very helpful guide. Starting Kobold HTTP Server on port 5001 Hello. So now its much closer to the TPU colab, and since TPU's are often hard to get, don't support all models and have very long loading times this is just nicer to use for people. KoboldAI is not an AI on its own, its a project where you can bring an AI model yourself. e. But luckily for you the post you replied to is 9 months old and a lot happens in 9 months. It's how the model is split up, not GB. As a beginner to chat ai's I really appreciate it you explaining everything in so much detail. I am new to the concept of AI storytelling software, sorry for the (possible repeated) question but is that GPU good enough to run koboldAI? Before even launching kobold/tavern you should be down to 0. 00 GiB total capacity; 4. ai which was able to run stable diffusion in GPU mode for Hi everyone I have a small problem with using kobold locally. 5GB (I think it might not actually be that consistent in practice but close enough for estimating the layers to put onto GPU). This "easier" version doesn't work for me so I don't know really. kobold-client-plugin does not support multiple instances connected to the same server - this convertible instance then As far as I know half of your system memory is marked as "shared GPU memory". StableAudio — AI Music Has Entered The Game. It offloads as many layers of the model as possible to your GPU, then loads the rest into your use the following search parameters to narrow your results: subreddit:subreddit find submissions in "subreddit" author:username find submissions by "username" We would like to show you a description here but the site won’t allow us. My GPU/CPU Layers adjusting is just gone to be replaced by a "Use GPU" toggle instead. Or check it out in the app stores using the GPU but not the Neural Engine. 58 GiB already allocated; 98. If you use --usevulkan 0 1 it would use GPU 0 and GPU 1. Anyway, for some I fired it up as remote, loaded the model (have tried both 13B and 6. Edit 2: Using this method causes the GPU session to run in the background, and then the session closes after a few lines. I had a failed install of Kobold on my computer PCI-e is backwards compatible both ways. 7 GB during generation phase - 1024 token memory depth, 80 tokens output length). **So What is SillyTavern?** Tavern is a user interface you can install on your computer (and Android phones) that allows you to interact text generation AIs and chat/roleplay with characters you or the community create. I did all the steps for getting the gpu support but kobold is using my cpu instead. Q2: Dependency hell Start by trying out 32/0/0 gpu/disk/cpu. Actions take about 3 seconds to get text back from Neo-1. I read that I wouldn't be capable of running the normal versions of Kobold AI with an AMD GPU so I'm using Koboldcpp is this true? There's really no View community ranking In the Top 10% of largest communities on Reddit. You can also run a cost benefit analysis on renting gpu time vs buying a loca GPU. I was unaware that support for AI frameworks on AMD cards is basically non-existent if you're running something like KoboldAI on a Windows PC, though. cpp works pretty well in windoes and seems to use the gpu to some degree. I have three questions and wondering if I'm doing anything wrong. It's not a waste really. I currently use MythoMax-L2-13B-GPTQ, which maxes out the VRAM of my RTX 3080 10GB in my gaming PC without blinking an eye. ai, and even that didnt manage to work - the Vulkan version. For watherver reason Kobold can't connect to my GPU, here is something funny though It used to work fine. My old video card is a GTX970. . I. The reason its not working is because AMD doesn't care about AI users on most of their GPU's so ROCm only works on a handful of them. dev, which seems to use RAM and the GPU on windows. A n 8x7b like mixtral won’t even fit at q4_km at 2k context on a 24gb gpu so you’d have to split that one, and depending on the model that might The problem you are having is the lack of the GPU combined with a 6B model, in the 0. 56 MiB free; 4. 30/hr, you’d need to rent 5,000 hours of GPU time to equal the cost of a 4090. depending on your cpu and model size the speed isn't too bad. Or check it out in the app stores the model selection on the ColabKobold GPU page isn't showing any of the NSFW models anymore, at least not for me. I tried their Nod. It's a measure of how much the numbers have been truncated to make it smaller. cpp, KoboldCpp now natively supports local Image Generation!. Tried to allocate 50. This link should open up kobold ai. Running on two 12GB cards will be half the speed of running on a single 24GB card of the same GPU generation. I used to have a version of kobold that let me split the layers between my GPU and CPU so i could use models that used more VRAM than my GPU could handle, and now its completely gone. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app Get the Reddit app Scan this QR code to download the app now. I also made sure there wasn't steam, razer etc running in the background. Before you set it up there is a lot of confusion about the kind of hardware people need because AI is a lot heavier to run than video games. Reply reply TOPICS /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind users from the Tried to allocate 100. kobold works better ahaha /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation Kobold will give You the option to split between GPU/CPU and RAM (Don't use disk cache). 00 GiB total capacity; 5. technical papers, machine learning, where to find resources and tools, how to develop AI/ML projects, AI in business Without Linux you'd probably need to put a bit less on the GPU but it should definately work. Fit as much on the GPU as you can. It doesn't use the GPU or its memory. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and Edit btw I want to save your post but reddit is being a dick and your picture is super white I can't hit the darn thing So after some tinkering around I was actually able to get Kobold AI working on Silly Tavern. So given your large budget get a 3090 (I'd personally wait until you can get them closer to msrp because right now you'd spend your entire budget while you should be spending half that in a normal market). koboldai. If you have a specific Keyboard/Mouse/AnyPart that is doing something strange, include the model number i. 9 GB and so on and so forth, it seems every back and forth increases my memory usage by . Sort by: Best. If you try to put the model entirely on the CPU keep in mind that in that case the ram counts double since the techniques we use to half the ram only work on the GPU. If you check your system specifications it will generally list the GPU you have in your system (along with CPU, motherboard, RAM and so on, but we just care about the GPU here), unless you have something highly custom and fairly exotic. Info: Ryzen 5 3600xt, 16gb ram, Nvidia 3090. I am not sure if this is potent enough to run koboldAI, as system req are nebulous. Smaller versions of the same model are dumber. I'm thinking about converting the models to CoreML, and writing a simple Mac/iOS client for that, to see how it runs when given access to the Apple Neural Engine. If you set them equal then it should use all the vram from the GPU and 8GB of ram from the PC. You will have to toy around with it to find what you like. Is there any alternative to get the software required for Kobold AI? Share Add a Comment. net. /r/StableDiffusion is back open after the protest of Reddit killing open API access Which model gpu is the best for nsfw ai chat? This one is pretty great with the preset “Kobold (Godlike)” and just works really well without any other adjustments. The timeframe I'm not sure. Kobold requires at least 16 of it if you want it to work stable. (New reddit? Click 3 dots at end of this message) Privated to protest Reddit's upcoming API changes. However, during the next step of token generation, while it isn't slow, the GPU use drops to zero. Taking the plunge on 2x Tesla P40's for Kobold AI, etc /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will A place to discuss the SillyTavern fork of TavernAI. View community ranking In the Top 10% of largest communities on Reddit. So you can get a bunch of normal memory and load most of it into the shared gpu memory. As an addendum, if you get an used 3090 you would be able to run anything that fits in 24GB and have a pretty good gaming GPU or for anything else you wanna throw at it. Recently i downloaded Kobold AI out of curiosity and to test out some models. Even if you don't have a good GPU, you can run For anyone struggling to use kobold Make sure to use the GPU collab version, and make sure the version is United. Is there a way for the Lite version to utilise the GPU instead of only the CPU? Official Reddit community of Termux project. This subreddit has gone Restricted and reference-only as part of a mass protest against Reddit's recent API changes, which break third-party apps and moderation tools. I'm very new to Kobold AI, and was hoping someone could tell me how to go about fine-tuning my own model(s)? I mean there's a computer somewhere with a powerful GPU and you SSH into it or something to do the work on that computer instead of your own. You won't get a message from google, but the Cloudfare link will lose connection. Yes, Kobold cpp can even split a model between your GPU ram and CPU. ) llama_model_load_internal: offloading non-repeating layers to GPU llama_model_load_internal: offloaded 33/33 layers to GPU llama_model_load_internal: total VRAM used: 3719 MB llama_new_context_with_model: kv self size = 4096. 5-3 range but doesn’t follow the colab A place to discuss the SillyTavern fork of TavernAI. 32 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split Also don’t use disk cache! It’s very very slow. Haven't been able to get Kobold to recognize my GPU . I am running PygmalionAI 6B version with the same graphics card, in 8-bit mode. At the bare minimum you will need an Nvidia GPU with 8GB of VRAM. I'm wondering what the differences will be. 2/6GB for built in vram. It's pretty cheap for good-enough-to-chat GPU horsepower. It should open in the browser now. I currently rent time on runpod with a 16vcore CPU, 58GB ram, and a 48GB A6000 for between $0. But even with enough RAM, you'll probably gonna have to wait for >minute for just one response, so without GPU playing Kobold is still pain. Anybody have an idea how to quickly fix this problem ? Running on GPU is much faster, but you're limited by the amount of VRAM on the graphics card. This is much slower though. 00 GiB total capacity; 7. Then I saw SHARK by Nod. It's almost always at 'line 50' (if that's a thing). Or check it out in the app stores TOPICS. Don't fill the gpu completely because inference will run out of memory. The model requires 16GB of Ram. safetensors file should be about 4. You want to make sure that your GPU is faster than the CPU, which in the cases of most dedicated GPU's it will be but in the case of an integrated GPU it may not be. He's talking about Kobold. It's usable. ) and It worked fine for a while . is the "quantization" of the model. 42 MiB free; 7. However, the post that finally worked took a little over two minutes to generate. Valheim; Genshin Impact sure but I think if you let it spill into "shared GPU memory" then it's going to have to swap out out to get the gpu to process it, where if you offload layers to cpu then the cpu handles it All LLMs should have some ability to "remember", but obviously, the smaller models have worse memory, and likely worse than character AI. I've tried They are the best of the best AI models currently available. (VAM + AI in VR being my ultimate goal). You can rent GPU time on something like runpod. GPU-primary performance is worlds above CPU Kobold AI utilises my GPU and can respond to something that takes Kobold AI Lite 2-3 minutes, in under 10 seconds. While the P40 is for AI only. Probably because I don't own a compatible AMD GPU to compile it for. GPUs and TPUs are different types of parallel processors Colab offers where: GPUs have to be able to fit the entire AI model in VRAM and if you're lucky you'll get a GPU with 16gb VRAM, even 3 billion parameters models can be 6-9 gigabytes in size. Look in the model page the gptq used for quantization. You can use kobold lite and let other kind folks in the horde do the generation for you. bat, it says no gpu was found. Download the KoboldCPP . Or check it out in the app stores TOPICS CUDA out of memory. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will I have a i7, 12 g ram, Nvidia gtx1050 I've been installing kobold ai to use the novel models. If we list it as needing 16GB for example, this means you can probably fill two 8GB GPU's evenly. I just started using Kobold AI now that Lite is a thing since I never could get it to work on the old Colab for me and I was able to use the other method using Colab with Kobald AI. If you want to follow the progress, come join our Discord server! Members Online /r/StableDiffusion is back open after the protest of Windows takes at least 20% of your GPU (and at least 1GB). io. But I have more recently been using Kobold AI with Tavern AI. The only difference is the size of the models. Note: Reddit is dying due to terrible leadership from CEO /u/spez. Or you can choose less layers on the GPU to free up that extra space for the story. Run out of VRAM? try 16/0/16, if it works then 24/0/8, and so on. 6-Chose a model. Sort by: Not just that, but - again without having done it - my understanding is that the processing is serial; it takes the output from one card and chains it into the next. Ahahaha. A place to discuss the SillyTavern fork of TavernAI. For GPU users you will need the suitable drivers installed, for Nvidia this will be the propriatary Nvidia driver, for AMD users you will need a compatible ROCm in the kernel and a compatible GPU to use this method. r/NovelAi. 5-2 tokens per second seems slow for a recent-ish GPU and a small-ish model, and the "pretty beefy" is pretty ambiguous. To do that, click on the AI button in the Kobold ai Browser window and now select The Chat Models Option, in which you should find all PygmalionAI Models chose a model that fits in your RAM or VRAM if you have a Supported Nvidia GPU. Disk cache can help sure, but its going to be an incredibly slow experience by comparison. With minimum depth settings you need somewhat more than 2x your model size in VRAM (so 5. 7B-Nerys-v2 that would mean 32 layers on the GPU, 0 on disk cache. It should be about 41GB (welcome to local AI, hope you have good internet!). The . Context size 2048. You may also have tweak some other settings so it doesn't flip out. I think I had to up my token length and reduce the WI depth to get it I'd personally hold off on buying a new card in your situation as Vulkan is in the finishing stages and should allow the performance on your GPU to increase a lot in the coming months without you having to jump trough ROCm hoops. I've managed about four inputs via SillyTavern before cpp crashes outright, and subsequent prompts (with only about 380 Hey all. it turns out torch has this command called: torch. 00 MB Load Model OK: True Embedded Kobold Lite loaded. 3GB. To run the model fully from GPU, it needs to fit in the VRAM. A few days ago, Kobold was working just fine via Colab, and across a number of models. The issue this time is that I don't know how to navigate KoboldAI to do that. If I were in your shoes, I'd consider the price difference of selling a I'm gonna mark this as NSFW just in case, but I came back to Kobold after a while and noticed the Erebus model is simply gone, along with the other one (I'm pretty sure there was a 2nd, but again, haven't used Kobold in a long time). bat to start Kobold AI. Similarly the CPU implementation is limited by the amount of system RAM you have. 00 MiB (GPU 0; 10. You can use it to write stories, blog posts, play a text adventure game, use it like a chatbot First I think that I should tell you my specs. I have --useclblast 0 0 for my 3080, but your arguments might be different depending on your hardware configuration. If you're running a local AI model, you're going to need either a mid-grade GPU (I recommend at least 8GB VRAM) or a lot of RAM to run CPU inference. I followed the readme to the letter, but was unable to get Kobold to recognize my RTX 3070. Google changed something, can't quite pinpoint on why this is suddenly happening but once I have a fix ill update it for everyone at once including most unofficial KoboldAI notebooks. I'm pretty new to this and still don't know how to use a AMD GPU. To full offload leave everything default but with 99 layers. __main__:device_config:916 - Nothing assigned to a GPU, reverting to CPU only mode You are using a model of type gptj to instantiate a model of type gpt_neo. 5-Now we need to set Pygmalion AI up in KoboldAI. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper A second question would be - I assume that I will need to updgrade to using paid AWS "instances" - is it worth it ? I've seen its possible to install a kobold ai on my pc but considering the size of the NeoX Version even with my RTX4090 and 32GB Ram I think I will be stuck with the smaller modells. I've reisntalled both kobold and python ( including torches etc. Most 6b models are even ~12+ gb. 32 GiB already allocated; 0 bytes free; 5. I am still running a 10 series GPU on my main workstation, they are still relevant in the gaming world and cheap. KoboldAI uses this command, but when I tried this command out on my normal python shell, it returned true, however, the aiserver doesn't. It was running crazy slow, no out put after more than 15 min other than 2 words and it was running off of cpu only. As of a few hours ago, every time I try to load any model, it fails during the 'Load Tensors' phase. I can fill my RTX 3060's VRAM with many layers with cuBLAS using CUDA and still only utilize 30% of its power. So if you're loading a 6B model which Kobold estimates at ~16GB VRAM used, each of those 32 layers should be around 0. I don't want to split the LLM across multiple GPUs, but I do want the 3090 to be my secondary GPU and leave my 4080 as the primary available for other things. With 10 layers on the GPU my response times are around 1 minute with a 1700X overclocked to 3,9GHz. Sadly my tiny laptop cannot run Kobold AI or I'd do it myself. More posts you may like TOPICS. 00 MiB (GPU 0; 6. I read that I wouldn't be capable of running the normal versions of Kobold AI Kaggle works in a similar way to google colab but you get more GPU time (30 hours a week) and it is more stable. I bought an used graphics card. There are two options: KoboldAI Client: This is the "flagship" client for Kobold AI. It requires GGML files which is just a different file type for AI models. Lowering the "bits" to 5 just means it calculates using shorter numbers, losing precision but reducing RAM requirements. I tried Pygmalion-350m and Pygmalion-1. This makes it so I'm overloading my 2 GPUs attempting to run PygmalionAI 6B model; Could someone help me with a permanent fix? Kobold is automatically leveraging both cards for compute, and I can watch their VRAM fill up as the model loads, but despite pushing all 33 layers onto the GPU(s) I've also seen the system memory get maxed out as well. How launch it on kobold AI and tavern Tried to build kobold from source for AMD GPU using ROCm on Windows what can we do. 7B models will work better speed wise since those will fit completely. Then, make sure you’re running the 4 bit kobold interface, and have a 4bit model of pygb. KoboldAI not using my GPU . 7B models take about 6GB of VRAM, so they fit on your GPU, the generation times should be less than 10 seconds (on my RTX 3060 is 4 s). The session closes because the GPU session exits. We have ways planned we are working towards to fit full context 6B on a GPU colab. 3b models. If you have more VRAM than the PyTorch_model. Shared GPU Memory: 1. Ordered a refurbished 3090 as a dedicated GPU for AI. 7/31. (newer motherboard with old GPU or newer GPU with older board) Your PCI-e speed on the motherboard won't affect koboldAI run speed. 5-3B/parameter so if I had to guess, if there’s an 8-9 billion parameter model it could very likely run that without problem and it MIGHT be able to trudge through the 13 billion parameter model if you use less intensive settings (1. The model is also small enough to run completely on my VRAM, so I want to know how to do this. 34 GiB already allocated; 13. Reply reply Top 7% Rank by size . Or check it out in the app stores Kobold isn't using my GPU at all Share Add a Comment. So you will need to reserve a bit more space on the first GPU. Models seem to generally need (for recommendation) about 2. The only other option I have heard of for AMD GPU's is to get torch set up with AMD ROCM, however I have no experience with it, and I I want to use a 30b on my RTX 6750 XT + 48GB RAM. in general with gguf 13b the first 40 layers are the tensor layers, these are the model size split evenly, the 41st layer is the blas buffer, and the last 2 layers are the kv cache (which is about 3gb on its own at 4k context) For hypothetical's sake, let's just say 13B Erebus or something for the model. Or check it out in the app stores TOPICS GPU access is given on a first-come first-serve basis, so you might get a popup saying no GPUs are available. I’ve already tried setting my GPU layers to 9999 as well as to I used the readme file as an instruction, but I couldn't get Kobold Ai to recognise my GT710. Valheim; Genshin Impact Get the Reddit app Scan this QR code to download the app now. If your answers were yes, no, no, and 32, then please post more detailed specs, because 0. And likewise we only list models on the GPU edition that the GPU edition can run. Subreddit for the in-development AI storyteller NovelAI. Next more layers does not always mean performance, originally if you had to many layers the software would crash but on newer Nvidia drivers you get a slow ram swap if you overload If you select a model from the AI menu and wait a few seconds for it to download the right config file does it show that slider along with a slider for your GPU? /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind users from the site. If it’s bigger than your amount of GPU VRAM, you can decrease the first slider, so more layers get loaded into RAM. 4 GB to 4. kobold. So, I found a pytorch package that can run on Windows with an AMD GPU (pytorch-directml) and was wondering if it would work in KoboldAI. Share your Termux configuration, custom utilities and usage experience or help others troubleshoot issues. The -hf versions can only run on the GPU version, and the GPU version will not work unless you have a suitably new Nvidia GPU. If Your PC can handle it, You can also use 4bit LLAMA models for Your PC, which uses the same amount of processing power but just plain better. To do that, click on the AI button in the KoboldAI browser window and now select the Chat Models Option, in which you should find all PygmalionAI Models. I open Kobold AI and I don't see Google Colab as a model, but number 8, Custom Neo, lists Horni. Some of my inputs didn't go through because I had already used all of my 12gb of vram. https://lite. Heres the setup: 4gb GTX 1650m (GPU) Intel core i5 9300H (Intel UHD Graphics 630) 64GB DDR4 Dual Channel Memory (2700mhz) The model I am using is just under 8gb, I noticed that when its processing context (koboldcpp output states "Processing Prompt [BLAS] (512/ xxxx tokens)") my cpu is capped at 100% but the integrated GPU doesn't seem to be doing Originally the GPU colab could only fit 6B models up to 1024 context, now it can fit 13B models up to 2048 context, and 20B models with very limited context. In other places I see it’s better to offload mostly to gpu but keep some on cpu. And the AI's people can typically run at home are very small by comparison because it is expensive to both use and train larger models. chat settings, changed the default AI service to Kobold, left the default preset to none (have also First I think that I should tell you my specs. bin file is in size, you can set all layers to GPU (first slider) and leave the second slider at 0. I'm using mixtral-8x7b. Gaming but its currently not in the UI. Keep in mind you are sending data to other peoples KoboldAI when you use this so if privacy is a big concern I don't agree, his GPU is being utilized according to the screenshots. Tried to allocate 14. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper Kobold runs on Python, which you cannot run on Android without installing a third-party toolkit like QPython. In today's AI-world, VRAM is the most important parameter. So doable? Absolutely if you have enough VRAM. Best. https://www. Whenever I run play. isavailable(). I've tried both koboldcpp (CLBlast) and koboldcpp_rocm (hipBLAS (ROCm)). It does require about 19GB of VRAM for the full 2048 context size, so it may be tough to get this running without access to a 3090 or better. In my experience, the 2. If I put that card in my PC and used both GPUs, would it improve performance on 6B models? /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind Get the Reddit app Scan this QR code to download the app now. 0 x16 GPU, because prompt ingestion bottlenecks to PCIE bus bandwidth. Or check it out in the app stores TOPICS I have been trying to get into this AI thing, but I tried to allocate koboldAi with 2 different models, with Pygmalion and GPT-Neo-2. If you use GGML models (ie Okay, so I made a post about a similar issue, but I didn't know that there was a way to run KoboldAI Locally and use that for VenusAI. Possibly full context 13B and perhaps even 20B again. 16 version that is not supported. For system ram, you can use some sort of process viewer, like top or the windows system monitor. Get the Reddit app Scan this QR code to download the app now. Docker has access to the GPUs as I'm running a StableDiffusion container that utilizes the GPU with no issues. Or check it out in the app stores TOPICS set up a pod on a system with a 48GB GPU (You can get an A6000 for $. 30/hr depending on the time of day. I've redone the entire installation process with different versions of Python If you have a beefy PC with a good GPU, you can just download your AI model of choice, install a few programs, and get the whole package on your own PC so you can play offline. Let's assume this response from the AI is about 107 tokens in a 411 character response. 4 and 5 bit are common. Or check it out in the app stores I'm running Kobold with GPU support on an RTX2080. Tell me if you get it working! This command will launch the kobold Lite client and load the model using the 8K context length. It has the same, if not better, community input as NovelAI, as you can talk directly to the devs at r/KoboldAI with suggestions or problems. As i am an AMD user I need to focus on RAM, you can check both Get the Reddit app Scan this QR code to download the app now. 7B models are the maximum you can do, and that barely (my 3060 loads the VRAM to 7. Valheim; Genshin Impact Running GPT-NeoX 20B model on RTX 3090 with 21 layers on GPU and 0 layers on Disk Cache but wondering if I should be using Disk Cache for faster generations? (currently 1 token per 1 second) All I have are AMD Gpu around and I would prefer running this in docker to keep it isolated from the rest of the system. cuda. 4GB), as the GPU uses 16-bit math. An unofficial place to discuss the unfiltered AI chatbot Pygmalion, as well as other open-source AI chatbots Subreddit has gone dark until June 14th to protest against Reddit's API changes Members Online. We don't allow easy access to the smaller models on the TPU colab so people do not waste TPU's on them. Then also make sure not much is using the GPU in the background beforehand. (Or it can run Kobold but no models. You can use it to write stories, blog posts, play a text adventure game, use it like a chatbot and more! In some cases it might even help you with an assignment or programming task (But always make sure The offline routines are completely different code than the one for the colab instance, and while the colab instance loads the model directly into the GPU ram while supporting the half mode that makes it ram friendly, the local routines seem to load A place to discuss the SillyTavern fork of TavernAI. 3B. 6b works perfectly fine but when I load in 7b into KoboldAI the responses are very slow for some reason and sometimes they just stop working. 2023-05-15 21:20:38 INIT | Searching | GPU support 2023-05-15 21:20:38 INIT | Not Found | GPU support 2023-05-15 21:20:38 INIT | Starting | Transformers" The model is loading into the RAM instead of my GPU. Horde will allow you to contribute your own GPU (or any other Kobold instance) to the community so others can use it to power KoboldAI. 49/hr with spot pricing) with the Thanks to the phenomenal work done by leejet in stable-diffusion. I think mine is set to 16 GPU and 16 Disk. A phone just doesn't have the computational power. Koboldcpp is not using the graphics card on GGML models! Hello, I recently bought an RX 580 with 8 GB of VRAM for my computer, I use Arch Linux on it and I wanted to test the Koboldcpp to see how the results looks like, the problem isthe koboldcpp is not using the ClBlast and the only options that I have available are only Non-BLAS which is Before you set it up there is a lot of confusion about the kind of hardware people need because AI is a lot heavier to run than video games. anyone know if theres a certain version that allows this or if im just being a huge idiot for not enabling some I want to make an AI assistant (With TTS and STT). I notice watching the console output that the setup processes the prompt * EDIT: [CuBlas]* just fine, very fast and the GPU does it's job correctly. 55 GiB reserved in total by PyTorch) I have an nvidia GPU that has sufficient VRAM to run the ai, however the nvidia GPU is assigned as GPU 1, and from what I understand the program is using the intergrated GPU which is GPU 0. 6B already is going to give you a speed penalty for having to run part of it on your regular ram. When I replace torch with the directml version Kobold just opts to run it on CPU because it didn't recognize a CUDA capable GPU. With your specs I personally wouldn't touch 13B since you don't have the ability to run 6B fully on the GPU and you also lack regular memory. Internet Culture (Viral) Amazing Kobold ai isn't using my gpu . It was a decent bit of effort to set up (maybe 25 mins?) and then takes a decent bit of effort to run (because you have to prompt it in a more specific way, rather than GPT-4 where you can be really lazy with how you write the prompts and it still gets AMD GPU driver install was confusing, this youtube video explains it well "How To Install AMD GPU Drivers In Ubuntu ( AMD Radeon Graphics Drivers For Linux )" by SSTec Tutorials When creating a directory for KoboldAI, do not use The AI always takes around a minute for each response, reason being that it always uses 50%+ CPU rather than GPU. it shows gpu memory used. Use the regular Koboldcpp version with CLBlast, that one will support your GPU. I'm going to be installing this GPU in my server PC, meaning video output isn't a Now we need to set Pygmalion AI up in Kobold AI. If you want to follow the progress, come join our Discord server! /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers A 13b q4 should fit entirely on gpu with up to 12k context (can set layers to any arbitrary high number) you don’t want to split a model between gpu and cpu if it comfortably fits on gpu alone. when you load the model, load in 22 layers in GPU, and set your context token size in tavern to 1500, and your response Get the Reddit app Scan this QR code to download the app now. Is a 3080 not enough for this? So if you want GPU accelerated prompt ingestion, you need to add --useclblast command with arguments for id and device. And probably the best option is to just run local. This is not supported for all configurations of models and can yield errors. For kobold ai the token size the number has to be less then 500 which is usually why the responses are shorter comspre to openai /r/GuildWars2 is the primary community for Guild Wars 2 on Reddit. runpod. My cpu is at 100% Share Add a Comment. 18 and $0. Please use our Discord server instead of supporting a company that Some say mixing the two will cause generation to be significantly slower if even one layer isn’t offloaded to gpu. I'm looking into getting a GPU for AI purposes. Man, I didn't realize how used to having access to the TPU I was, I'm literally testing it a couple of times a day to see if it's working again. /r/StableDiffusion is Are the GPU layers maxed? For let's say OPT-2. Internet Culture (Viral) Amazing; Animals & Pets I was wondering if there's any way to make the integrated gpu on the 7950x3d useful in any capacity in koboldcpp with my current setup? I mean everything works fine and fast KoboldCpp allow offloading layers of the model to GPU, either via the GUI launcher or the --gpulayers flags. Subreddit for the in-development AI storyteller For PC questions/assistance. 3-5 GB or so but after about 10 messages this increase starts to ramp up to about 1-2 GB sometimes, not all the time but just sometimes, but i watched it go from 2. It would not be using 28% of its power if no GPU acceleration was present. Db0 manages it, so he will ultimately be the arbiter of the rules as far as a need for contributions. It provides an Automatic1111 compatible txt2img endpoint which you can use within the embedded Kobold In GPU mode 16GB of system ram could squeeze it in your GPU but 32GB gives you space for the rest of your system. 7B), went into the agnai. NieR: Automata ending E GPU boots faster (2-3 minutes), but using TPU will take 45 minutes for a 13B model, HOWEVER, TPU models load the FULL 13B models, meaning that you're getting the quality that is otherwise lost in a quant. Gaming. 3 can run on 4GB which follows the 2. Hi, thanks for checking out Kobold! You can host the model on Google Colab, which will not require you to use your GPU at all. but it won't show image nah is not really good to run the program let alone the models as even the low end models requiere a bigger gpu, you have to use the collabs though if you want to do that i recommend using the tpu collab as is bigger and it gives better responses than the gpu collab in short 4gb is way to low to run the program using the collabs are the only way to use the api for janitor ai in My overall thoughts on kobold are - the writing quality was impressive and made sense in about 90% of messages, 10% required edits. If you want performance your only option is an extremely expensive AI Assuming you have an nvidia gpu, you can observe memory use after load completes using the nvidia-smi tool. I think that model actually use GPU but it slow because of disk cache, check VRAM usage in task manager on windows or by nvidia-smi on Linux. You should be seeing Originally we had seperate models, but modern colab uses GPU models for the TPU. When I'm generating, my CPU usage is around 60% and my GPU is only like 5%. Just set them equal in the loadout. gguf file. So for now you can enjoy the AI models at an ok speed even on Windows, soon you will hopefully be able to enjoy them at speeds similar to the nvidia users and users of the more expensive 6000 series where AMD does have driver support. For non-headless linux, cuda/desktop take about 1GB of VRAM. You can find them on Hugging Face by searching for GGML. exe from the That is because AMD has no ROCm support for your GPU in Windows, you can use https: So for now you can enjoy the AI models at an ok speed even on Windows, soon you will hopefully Ok I was able to load GPT-J 6b with 17 layers on GPU, 7 on CPU and 4 on disk cache, thanks! Next I will try to lower disk cache layers to see if I can put more on CPU. The biggest reason to go Nvidia is not Kobold's speed, but the wider compatibility with the projects. You can then start to adjust the number of GPU layers you want to use. If you want to run only on GPU, 2. Some implementations (I use the oobabooga UI) are able to use the GPU primarily but also offload some of the memory and computation 4-After the updates are finished, run the file play. uyoqiys ffes uzttfpxty kimctu fdycgg zak npdz vero qesc rirvdhn