Kobold cpp smart context. May 29, 2024 · 0 comments Return to top.

Kobold cpp smart context bin --usecublas --smartcontext which means to process context on GPU but do not offload layers because it will not give noticeable improvement. Basically, since Llama 2 can use 4096 tokens of context and being able to stretch it by up to 4x (as explained in your helpful Wiki), the context window is a lot bigger now. OPTIONAL: Submit Download stats (for measuring Restored support for ARM quants in Kobold (e. Consider a chatbot scenario and a long chat where old lines of dialogue need to be evicted from the context to stay within the (4096 #What is it? Smart Context is a SillyTavern extension that uses the ChromaDB library to give your AI characters access to information that exists outside the normal chat history context limit. Like all text generation models, KoboldAI has a token context limit (2048, the same as Oobabooga before their most recent update. Like maybe 5000 tokens. Low VRAM option enabled, offloading 27 layers to GPU, batch size 256, smart context off. cpp, it takes a short while (around 5 seconds for me) to reprocess the entire prompt (old koboldcpp) or ~2500 tokens (Ooba) at 4K context. It's a fork of Llama CPP that has a web UI and has features like world info and lorebook that can append info to the prompt to help the AI remember important info. There is already a Llama 13b pytorch with 32k context. 4+ (staging, latest commits), and I made sure I don't have any dynamic information added anywhere in the context sent for processing. 11. sending the new image while keeping the old one doesnt work either multiple images I'm a newbie when it comes to AI generation but I wanted to dip my toes into it with KoboldCpp. Cpp is a 3rd party testground for KoboldCPP, a simple one-file way to run various GGML/GGUF models with KoboldAI's UI. It’s really easy to setup and run compared to Kobold ai. "NEW FEATURE: Context Shifting (A. llama. TL;DR download larger . cpp has no support for this flag, and so this model cannot be For me, right now, as soon as your context is full and you trigger Context Shifting it crashes. If you want less smart but faster, there are other Yes it can be done, You need to do 2 things: Launch with --contextsize, e. The prompt processing is so absurdly slow without it that it makes GGML Kobold is more a story based ai more like novelai more useful for writing stories based on prompts if that makes any sense. For me, right now, as soon as your context is full and you trigger Context Shifting it crashes. Using the same model with the newest kobold. when 4096 is cut into “This feature utilizes KV cache shifting to automatically remove old tokens from context and add new ones without requiring any reprocessing. ” This means a major speed increase for people like me who rely on (slow) CPU inference (or big models). However, KoboldAI Lite is licensed under the AGPL v3. Tested the new version (1. It's a simple executable that combines KoboldLite UI with llama. cpp kv cache, but may still be relevant. cpp/kobold. Agent work with Kobold. In short, this reserves a portion of total context space (about 50%) to use as a 'spare KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models, inspired by the original KoboldAI. cpp quants seem to do a little bit better perplexity wise. Instead of using high-precision floating-point numbers (typically 32-bit floats), quantization converts these values to lower-precision formats, such as 16-bit, 8-bit, 4-bit or even lower-bit SillyTavern provides a single unified interface for many LLM APIs (KoboldAI/CPP, Horde, NovelAI, Ooba, Tabby, OpenAI, OpenRouter, Claude, Mistral and more), a mobile-friendly layout, Visual Novel Mode, Automatic1111 & ComfyUI API image generation integration, TTS, WorldInfo (lorebooks), customizable UI, auto-translate, more prompt options than you'd ever want or In the new version, generation is interrupted by the "Generating (30 / 512 tokens)exception: access violation reading 0x0000000000000000" I have a rx6600, I have changed the default settings, temperture, context size and I use Microstat v2 llama. cpp locally with a fancy web UI, persistent stories, editing tools, save formats, memory, world info, author's note, characters, scenarios and more with minimal setup. I used 1. cpp I have been playing around with Koboldcpp for writing stories and chats. # How is that useful? If you have a very long chat, the majority of the contents are outside the usual context window and thus unavailable to the AI when it comes to writing a response. bin file for big smart AI. For context size, the problem is that not all buffers scale The Plex Media Server is smart software that makes playing Movies, TV Shows and other media on your computer simple. The context-saving ability would be a HUGE help to this, by the way. ——— I feel RAG - Document embeddings can be an excellent ‘substitute’ for loras, modules, fine tunes. So there's always enough room for "context shifting" to go back. The best part is it runs locally and depending on the model, uncensored. (for KCCP Frankenstein, in CPU mode, CUDA, CLBLAST, or VULKAN) - kobold. The best part was being able to edit previous context and not seeing a GGUF slowdown as it reprocessed. It's tough to compare, dependent on the textgen perplexity measurement. cpp would re-tokenize everything after that position. So OP might be able to try that. Cpp, in Cuda mode mainly!) Since v1. You can use the included UI for stories For GGUF Koboldcpp is the better experience even if you prefer using Sillytavern for its chat features. 1. But Kobold not lost, It's great for it's purposes, and have a nice features, like World Info, it has much more user-friendly interface, and it has no problem with "can't load (no matter what loader I use) most of 100% working models". Notifications You must be signed in to change notification settings; Fork 360; Star 5. Discussion options KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models, inspired by the original KoboldAI. If youre looking for a chatbot even though this technically could work like a chatbot its not the most recommended Ooga/Tavern two different ways to run the AI which you like is based on preference or context. Smart Context is enabled via the command --smartcontext. And thanks to the API, it works perfectly with SillyTavern for the most comfortable chat experience. cpp: loading model from C:\AI\models\TheBloke_Guanaco-7B-SuperHOT-8K-GGML\guanaco-7b-superhot-8k. There is one more I should mention, the Strangely enough, I'm now seeing the opposite. I figure it would be appropriate to ask for compatibility to be added into Kobold, when time permits. Something about the implementation affects thing outside of just tokenization. Kobold evals the first prompt much faster even if we ignore any further context whatsoever. Advanced users should look into a pipeline consisting of Kobold-->SimpleProxyTavern-->Silly Tavern, for the greatest roleplaying freedom. Basically with cpu, you are limited to a) ram bandwidth b) number of cores. Next, I think it requires some setting in the UI, like response length, max distance, etc, because I think those depend on the purpose. cpp has continued accelerating (e. Does Obsidian Smart Connections work with programs like Text-Gen-UI or Kobold. The model is as "smart" as using no scaling at 4K, continues to form complex sentences and descriptions and doesn't go ooga booga mode. . cpp release should provide 8k context, but runs significantly slower. Merged optimizations from upstream Updated embedded Kobold Lite to v20. Now, I've expanded it to support more models and formats. This is self contained distributable powered by Environment and Context. GPU transcoding VRAM usage and I'm using 4096 context pretty much all the time, with appropriate RoPE settings for LLaMA 1 and 2. Things are changing at a breakneck pace. cpp KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models, inspired by the original KoboldAI. cpp, and adds a versatile KoboldAI API endpoint, additional format support, Stable Diffusion image generation, speech-to-text, backward compatibility, as well as a fancy UI with persistent Contextshift seems to only be working if the context size I set in sillytavern exceeds my setting in koboldcpp. Linux; Microsoft Windows; Apple MacOS; Android Context - Going too high might break your output once you reach your model's actual context limits. Croco. cpp --model model_33B. Considering that this model has been lucid so far, I am expecting to eventually hit the context limit of vanilla Kobold soon. cpp #441. In short KoboldCpp 1. The system ram bandwidth and it being shared between cpu/igpu is why igpu generally doesn't help - gen speed is mainly gb/s ram speed. The fastest GPU backend is vLLM, the fastest CPU backend is llama. There are f16 and q4_1 versions, and both of them return same wrong responses. 1k. cpp working reliably with my setup, but koboldcpp is so easy and stable, it makes AI fun again for me. I haven't done any synthetic benchmark but with this model context insanity is very clear when it happens. KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models, inspired by the original KoboldAI. That however doesn't work with very similar prompts that do not change in a linear time fashion, such as prompts altered by lore keywords or character cards in, for example silly tavern - that otherwise may be over 50% similar all of the time. **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. Use the one that matches your GPU type. cpp, and adds a versatile KoboldAI API endpoint, additional format support, Stable Diffusion image generation, speech-to-text, backward compatibility, as well as a fancy UI with persistent The responses would be relevant to the context, and would consider context from previous messages, but it tended to fail to stop writing, routinely responding with 500+ tokens, and trying to continue writing more, despite the token length target being around 250), and would occasionally start hallucinating towards the latter end of the responses. - rez-trueagi-io/kobold-cpp One FAQ string confused me: "Kobold lost, Ooba won. It will allow you to avoid almost all reprocessing. It does increases perplexity but should still work well below 4096 even on untuned models noromaid-v0. 00 MB Load Model OK: True Embedded Kobold Lite loaded. Run GGUF models easily with a KoboldAI UI. Otherwise, select the same settings you chose before. Does anyone have cuBLAS working with kobold on Linux with CUDA 11. A. The problem I'm having is that KoboldCPP / llama. You switched accounts on another tab or window. b1204e This Frankensteined release of KoboldCPP 1. 57. Analytics. cpp 3)Configuring the AGiXT Agent (AI_PROVIDER_URI, provider, and so on) Attempt to chat with an agent on the Agent Interactions tab; Expected Behavior. exe --model . cpp models are Larger for my same 8GB of VRAM (Q6_K_S at 4096 context vs EXL2 4. 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 In this video we quickly go over how to load a multimodal into the fantastic KoboldCPP application. cpp being shite and broken. cpp, KoboldCpp now natively supports local Image Generation!. cpp/model_adapter. Moreover, Kobold boasts an additional perk with its smart context cache. exllama also only has the overall gen speed vs l. out of curiosity, does this resolve some of the awful tendencies of gguf models too endlessly repeat phrases seen in recent messages? my conversations always devolve into Firewalla is dedicated to making accessible cybersecurity solutions that are simple, affordable, and powerful. When I moved from Ooba to KoboldCPP, Ooba did not support context caching, whereas Kobold already implemented smart context, with context caching introduced later. If the context overflows, it smartly discards half to prevent re-tokenization of prompts, in contrast to ooba, which simply forced to discard most cache whenever the first chat General Introduction. cpp and adds a versatile Kobold API endpoint, as well as a fancy UI with persistent stories, editing tools, save formats, memory, world info, author's note, characters, scenarios and everything Kobold and Kobold Lite have to offer. 5 version, I found the 1. This will allow Koboldcpp to perform Context Shifting, and Processing shouldn't take more than a second or two, making your responses pretty much instant, even with a big context like 16K for example. 3k. From what I have seen so far, this model is fairly smartbut it feels like it could use a finetune. Plus context size, correcting for windows making only 81% available, you're likely to need 90GB+. (There's also a 1. gguf ) and the context size ( 8192 ), 16GB VRAM would be plenty to run it with acceptable generation speed + currently it’s one of Dolly V2 3B is my favorite for Android but you'll need --smartcontext but do not use --highpriority. gguf. There have also been reported final tokens/second speed improvements for inference, so that's also grand!. Change the GPU Layers to your new, VRAM-optimized number (12 layers in my case). Extrapolate. safetensors fp16 model to load, Lorebooks/Memories, ST Smart Context, ST Vector Storage, set Example Dialogues to Always included. cpp. Enter the Number of Threads: 20. q4_K_S. Works pretty well for me but my machine is at its limits. (BTW: gpt4all is running this 34B Q5_K_M faster than kobold, it's pretty crazy) Some time back I created llamacpp-for-kobold, a lightweight program that combines KoboldAI (a full featured text writing client for autoregressive LLMs) with llama. Thanks to the phenomenal work done by leejet in stable-diffusion. " This means a major speed increase for people like me who rely on (slow) CPU inference (or big models). It can't form associations deeper than 1 step and often not even that. When I work with the “Llama3. q4_K_M. Our smart firewalls enable you to shield your business, manage kids' and employees' online activity, safely access the Internet while traveling, securely work What I like the most about Ollama is RAG and document embedding support; it’s not perfect by far, and has some annoying issues like (The following context) within some generations. Its context shifting was designed with things like Sillytavern in mind so if your not using things like Lorebooks and Vector Storage it can save Running Kobold. I didn't enable Smart Context or Context Shifting since I wanted to see how pure model memory would behave. g. A 3rd party testground for Koboldcpp, a simple one-file way to run various GGML models with KoboldAI's UI - bit-r/kobold. comments sorted by Best The above command puts koboldcpp into streaming mode, allocates 10 CPU threads (the default is half of however many is available at launch), unbans any tokens, uses Smart context (doesn't send a block of 8192 tokens if not needed), sets the context size to 8192, then loads as many layers as possible on to your GPU, and offloads anything else Currently, it's managing a whopping 64 tokens at most, often 32, before re-processing the entire context, which takes ages, even though the output itself takes one second. OPTIONAL: Build Latest Kobold (takes ~7 minutes) OPTIONAL: Build Latest Kobold (takes ~7 minutes) edit. And I was chatting for a while, so all the former tokens were sampled at some point in the same run. forked from ggerganov/llama. When you import a character card into KoboldAI Lite it automatically populates the right fields, so you can see in which style it has put things in to the memory and replicate it yourself if you like. I suppose it's supposed to condense the earlier text What is Smart Context? Smart Context is enabled via the command --smartcontext. To be fair, I am not that deep into llama. The output generation can I have the same problem when using llama. Reply Introducing llamacpp-for-kobold, run llama. safetensors fp16 model to load, KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models. The model has ingested about 10,000k of context from my system prompt and WorldInfo. Just select a compatible SD1. Using GPT-2 or NAI through ST resolves this, but often breaks context shifting. hopefully this has been helpful and if you've any questions feel free to ask! KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models. EvenSmarterContext) - This feature utilizes KV cache shifting to automatically remove old tokens from context and add new ones without requiring any reprocessing. ContextShift is always better than Smart Context on models that support it. I can't be certain if the same holds true for kobold. Renamed to KoboldCpp. tensorcores support) and now I find llama. bin file it will do it with zero fuss. For example, if Bob has a special shirt of invisibility that you define separately A place to discuss the SillyTavern fork of TavernAI. Kobold seems better when dealing with cutting the context, but Comprehensive documentation for KoboldCpp API, including setup instructions and usage guidelines. Although it has its own room for improvement, it's generally more So the best way to think of smart context is that it takes a "snapshot" of the memory at the point where the smart context triggers. I keep my context at 256 tokens and new tokens around 20. Is there a different way to install for CPP or am I doing something else wrong? Solidity is an object-oriented, high-level language for implementing smart contracts Members Online. 0 better but haven't tested much. The only downside is the memory requirements for some models and generation speed being around 65s with a 8gb model. 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. As it stands copying gfx1030 to gfx1031 outputs gibberish at times, the attached libraries should allow non-gibberish, sensible inference. With koboldcpp I can run this 30B model with 32 GB system RAM and a 3080 10 GB VRAM at an average around 0. 1–8B-Instruct-Q6_K. The recently released Bluemoon RP model was trained for 4K context sizes, however, in order to make use of this in llama. cpp that kobold. This is a feature from llama. It provides an Automatic1111 compatible txt2img endpoint which you can use within the embedded Kobold Lite, or in many other compatible frontends such as SillyTavern. I don't understand why this is even necessary. Just like the results mentioned in the the post, setting the option to the number of physical cores minus 1 was the fastest. cpp, and adds a versatile KoboldAI API endpoint, additional format support, Stable Diffusion image generation, speech-to-text, backward compatibility, as well as a fancy UI with persistent A 3rd party testground for KoboldCPP, a simple one-file way to run various GGML/GGUF models with KoboldAI's UI. cpp seems to process the full It adds the result at the top of the context as a "memory". How it works: When your context is full and you submit a new generation, it performs a text similarity check (getting A simple one-file way to run various GGML and GGUF models with KoboldAI's UI - koboldcpp/model_adapter. 1 all has the same issue. Now with When chatting with an AI character, I noticed that the context drop of 50% with smart context can be quite influential on the character's behavior (e. cpp change that causes the thread yielding to be conditional, instead, it always does it. Can someone please tell me, why the size of context in VRAM grows so much with layers? For example, if I have a model in GGUF with exactly 65 layers, then . gguf --usecublas --gpulaye And I don't use any lore, or extension that would add things to middle of the context. It happens with any prompt, any mode, many different models and has persisted through patches. I suggest enabling mirostat sampling in kobold when you launch it since it saves a lot of headache towards getting good text out of the models, and enabling Smart Context in kobold settings saves a lot of prompt processing time and speeds things up a lot. In terms of GPUs, that's either 4 24GB GPUs, or 2 A40/RTX 8000 / A6000, or 1 A100 plus a 24GB card, or one H100 (96GB) when that launches. cpp Configure Kobold CPP Launch Choose an option: Run Python Version; Run Binary Version; Enter your choice (1 or 2): 2. ) KoboldAI, on the other hand, uses "smart context" in which it will search the entire text buffer for things that it believes are related to your recently entered text. Here is the link to it, plus some 16k and 8k models. KoboldCPP Setup. I'm using a model to generate long conversations. My experience was different. I have brought this up many times privately with lostruins, but pinpointing the exact issue is a bit hard. There has been some hallucinating, but I am not sure if that is because of my preset. The Plex Media Server is smart software that makes playing Movies, TV Shows and other media on your forked from ggerganov/llama. cpp at rebase_170171 · Nexesenex/kobold. In general, assuming a 2048 context with a Q4_0 In essence, its a context aware translator that translates the current prompt into an answer and that's it. This improves prompt processing performance for me on my CPU which has Intel E-cores, and matches the old faster build I A 3rd party testground for Koboldcpp, a simple one-file way to run various GGML models with KoboldAI's UI - bit-r/kobold. 1. Open but the resposes from llama. cpp, and adds a versatile Kobold API endpoint, additional format support, Stable Diffusion image generation, backward compatibility, as well as a fancy UI with persistent stories, editing tools, save formats, memory, If I set the context size to any value (doesn't matter if I use GUI or manual) then n_ctx gets bigger then the configured value. Consider a chatbot scenario and a long chat where old lines of dialogue need to be evicted from the context to stay within the (4096 There has been increased granularity added to the context sizes with options for 3072 and 6144 added as well. but the 7b model was nearly instant in that context. cpp itself is struggling with context shifts and koboldcpp is not? Isn't koboldcpp built on top of llama. \MLewd-ReMM-L2-Chat-20B. It is a single self-contained distributable version provided by Concedo, based on the llama. With this koboldcpp version, just use the original models with increased context! I also experimented by changing the core number in llama. cpp, and adds a versatile KoboldAI API endpoint, additional format support, Stable Diffusion image generation, speech-to-text, backward compatibility, as well as a fancy UI with persistent Wait for the next version - there is going to be a much better version of smart context called Context Shifting. Code; Issues 195; Pull requests 0; 1024k context limit #877. So I hope this special edition will become a regular occurance since it's so helpful. 4-mixtral-instruct-8x7b-zloss. Can get more information, but generation will take longer and can have more opportunity for hallucinations: Disable Multiline /disable_multiline_response So far, I am using 40,000 out of 65,000 context with KoboldCPP. Increasing Context Size: Try --contextsize 4096 to 2x your context size! without much perplexity gain. context shifting works when you send the same image but is it possible to not have to reprocess the entire prompt when its the same other than the image? using the same instance of kobold with images resets the kvcache context shifting whenever a new image is used. For big models, AMX might become the best answer for the consumer. It doesn't matter how much of that context is used, behavior is the same for new chats with only a few hundred tokens or existing chats with 10k+ tokens. Some time back I created llamacpp-for-kobold, a lightweight program that combines KoboldAI (a full featured text writing client for autoregressive LLMs) with llama. It's certainly not just this context shift, llama is also seemingly keeping my resources at 100% and just really struggling with evaluating the first prompt to begin with. 7 tokens/sec. there is kobold ai lite it's a web browser based version that has access to the horde quality may vary depending on witch models are available Reply reply "This feature utilizes KV cache shifting to automatically remove old tokens from context and add new ones without requiring any reprocessing. cpp, and adds a versatile Kobold API endpoint, additional format support, backward compatibility, as well as a fancy UI with persistent stories, editing tools, save formats, memory, world info, author's note, characters, A simple one-file way to run various GGML and GGUF models with KoboldAI's UI - GitHub - LakoMoor/koboldcpp: A simple one-file way to run various GGML and GGUF models with KoboldAI's UI This particular one may also be related to updates in llama. Tested using RTX 4080 on Mistral-7B-Instruct-v0. Operating System. Giraffe v2 - 13b 32k I have tried to use models in this repo, but ggml files in this repo always returns '^^^^^'. Reply reply smart context, and context shifting. This page is community-driven and not run by or affiliated with Plex, Inc. The task of initial processing of a large context is much, MUCH better solved by preserving the model context on exit. cpp on ooba with my M1 Pro, 8 threads. Seems to me best setting to use right now is fa1, ctk q8_0, ctv q8_0 as it gives most VRAM savings, negligible slowdown in inference and (theoretically) minimal perplexity gain. You signed in with another tab or window. 33, you can set the context size to be above what the model supports officially. 6700XT/6800M Gfx1031 libraries for compilation of Kobold. If it starts spewing strange new words, or create strange "thought chains" - there is a possibility you're going over the model's max comfy temperature. Run koboldcpp. IceShaper. Note that this model is great at creative writing, and sounding smart when talking about tech stuff, but it sucks horribly at stuff like logic puzzles or (re-)producing factually correct in-depth answers about any topic I'm an I have reverted the upstream llama. I just got a new PC for AI, so now I'm finally on a 3090 as well, and am switching to Q8_0 for 13B models which takes The original GGML library and llama. cpp-frankensteined_experimental_v1. The memory will be preserved as the By doing the above, your copy of Kobold can use 8k context effectively for models that are built with it in mind. cpp llamacpp-for-kobold, a zero dependency KoboldAI compatible REST API interfacing with llama. You get llama. 0bpw at 4096 context -- The 4KM l. 17, 1. cpp, and adds a versatile Kobold API endpoint, additional format But smart context will chop off the start of the context windows. 1 + SillyTavern 1. Have fun. Kobold is very and very nice, I wish it best! <3 Hi, I've recently instaleld Kobold CPP, I've tried to get it to fully load but I can't seem to attach any files from KoboldAI Local's list of models. Out of curiosity, is it not possible to track tokenization separately? For example, if I update my chat at position 200, Kobold/llma. Code; Issues 246; Koboldcpp's main memory for things like context, etc that can Quantization, in the context of machine learning, refers to the process of reducing the precision of the numbers used to represent the model's parameters. After looking at the Readme and the Code, I was still not fully clear what all the input parameters meaning/significance is for the batched-bench example. IceShaper started this conversation in Ideas. It seems to me you can get a significant boost in speed by going as low as q3_K_M, but anything lower isnt worth it. 76 before. cpp, and adds a versatile KoboldAI API endpoint, additional format support, Stable Diffusion image generation, speech-to-text, backward compatibility, as well as a fancy UI with persistent I've noticed that the context shift mechanism with this model works somehow wrong, if not to say it doesn't work at all. cpp, and adds a versatile KoboldAI API endpoint, additional format support, Stable Diffusion image generation, speech-to-text, backward compatibility, as well as a fancy UI with persistent Moving the old, out of context text out of the text box, and submit again. exe as Admin. cu:255: src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16 <CRASH> GGML_ASSERT: U:\GitHub\kobold. why is it that llama. I don't think the q3_K_L offers very good speed gains for the amount PPL it adds, seems to me it's best to stick to the -M suffix k-quants for the best balance between performance and PPL. Offload 41 layers, turn on the "low VRAM" flag. Although it has its own A bit off topic because the following benchmarks are for llama. cpp, and adds a versatile KoboldAI API endpoint, additional format support, Stable Diffusion image generation, speech-to-text, backward compatibility, as well as a fancy UI with persistent KoboldAI users have more freedom than character cards provide, its why the fields are missing. Now it loads and works. I'm using SillyTavern's staging branch as my frontend. Environment and Context. CPP on locally run models? I can't seem to get it to work and I'd rather not use OpenAI or online third party services. When I was trying out the q6 version of Airoboros through Kobold, the memory use on my 64gb of RAM reached 99% in the task manager. Erases the current conversation and returns the context window to a clean slate. Barking, Doorbell, Chime, Muzak) In need of help with Kobold CPP -Conversation disappering. \koboldcpp. cpp with different LLM models; Checking the generation of texts LLM models в Kobold. I am using the prebuilt koboldcpp 1. cpp? it employs 'smart context' which sheers the oldest part of the kv cache and KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models, inspired by the original KoboldAI. 43 is just an updated experimental release cooked for my own use and shared with the adventurous or those who want more context-size under Nvidia CUDA mmq, this until LlamaCPP moves to a quantized KV cache allowing also to integrate within the If you open up the web interface at localhost:5001 (or whatever), hit the Settings button and at the bottom of the dialog box, for 'Format' select 'Instruct Mode'. Temperature - Pretty much every model can work decently at temperature of 1. After the context been used up, my generation speed just dropped from 8 tokens/sec to 0. 8? Everything compiles fine but I get a generic "unknown CUDA error" when I enable it. CuBLAS = Best performance for NVIDA GPU's 2. Hopefully improvements can be made as it would be great to have the features I couldn't get oobabooga's text-generation-webui or llama. 6 reread the entire context after each 8 token output however, now it manages to pump out 8x4 tokens the first time, before returning to one 8 token output, and “This feature utilizes KV cache shifting to automatically remove old tokens from context and add new ones without requiring any reprocessing. Note that you'll have to increase the max context in the Kobold Lite UI as well (click and edit the number text field). You can then start to adjust the number of GPU layers you want to use. For most usage, KCPP is just far nicer and easier than LCPP, but they way they generate responses to prompts is essentially identical. cpp fork to begin with, but all of these improvements that people do This is the default tokenizer used in Llama. cpp tho. When chatting with an AI character, I noticed that the context drop of 50% with smart context can be quite influential Now do your own math using the model, context size, and VRAM for your system, and restart KoboldCpp: If you're smart, you clicked Save before, and now you can load your previous configuration with Load. 1) with the model from the initial post. cpp Kobold. It's a single self contained distributable from Concedo, that builds off llama. cpp\ggml-cuda\rope. Note that this model is great at creative writing, and sounding smart when talking about tech stuff, but it sucks horribly at stuff like logic puzzles or (re-)producing factually correct in-depth answers about any topic I'm an Context Matters. KoboldCpp is an easy-to-use AI text generation software for GGML and GGUF models, inspired by the original KoboldAI. [Context Shifting: Erased 140 tokens at position 1636]GGML_ASSERT: U:\GitHub\kobold. Is Try using Kobold CPP. As far as models go, I like Midnight Miqu 70B q4_k_m. --contextsize 4096, this will allocate more memory for a bigger context Manually override the slider values in kobold Lite, this can be easily done by just clicking the textbox above the slider to input a custom value (it is editable). cpp via ctypes bindings #315 LostRuins started this conversation in Show and tell llamacpp-for-kobold, a zero dependency KoboldAI compatible REST API interfacing with llama. (for Croco. The text was updated successfully, but these errors were encountered: Kobold set up right ingests in 60 seconds, and then with shifting I basicaly get replies starting in less than a second after that. Reload to refresh your session. cpp with a fancy UI, persistent stories, editing tools, save formats, memory, world info, author’s note, characters, scenarios and everything Kobold and Kobold Lite have to offer. Fixed a bug that caused context corruption when aborting a generation while halfway processing a prompt; Added new field suppress_non_speech to Whisper allowing banning "noise annotation" logits (e. In short, this reserves a portion of total context space (about 50%) to use as a 'spare buffer', permitting you to do prompt processing much less Covers everything from "how to extend context past 2048 with rope scaling", "what is smartcontext", "EOS tokens and how to unban them", "what's mirostat", "using the command Even with full GPU offloading in llama. The PPL for those three q#_K_M are pretty impressive if we compare it If I enable vertex storage, even at a depth of 2, the inserted messages push off enough context to cause a near-full regeneration. kobold. Q6_K. CPP Frankenstein is a 3rd party testground for KoboldCPP, a simple one-file way to run various GGML/GGUF models with KoboldAI's UI. Everything else is a disadvantage. 43. You should expect less VRAM usage for the same context, allowing you to experience higher contexts with your current GPU. 7. Failure Information (for bugs) When using Kobold CPP, the output generation becomes significantly slow and often stops altogether when the console window is minimized or occluded by clicking on a web browser window. Currently, you can set the --contextsize to any of these values [512,1024,2048,3072,4096,6144,8192] while you have full control of setting the RoPE Scale to whatever you want with --ropeconfig. cpp is integrated into oobabooga webUI as well, and if you tell that to load a ggml. ) It's "slow" but extremely smart. I know Kobold IS a llama. If models are becoming that reliable with long context, then it might be time to add support for a bigger size. 52. One File. I set the "Amount to Generate" to 512. While the models do not work quite as well as with LLama. bin llama_new_context_with_model: kv self size = 4096. Smart_Context: edit. I get a max generation time of 40seconds, but that's only every 4th or 5th message when smart context resets. This is a new behaviour in my opinion since I updated. edit. Is there a way to add some "padding" to Vertex Storage that is somewhat of a reserved space for future messages to live? That way prompt reprocessing starts at the depth it is added rather than reprocessing the At 16K now with this new method, there are 0 issues from my personal testing. You can see the huge drop in final T/s when shifting doesn't happen. May 29, 2024 · 0 comments Return to top. As soon as smart context is refreshed, it's back to normal. For the model I’m using ( Meta-Llama-3. Reality check: Yes I definitely was keeping enough text in the text box. It's a single self-contained distributable from Concedo, that builds off llama. 1024k context limit #877. This release brings an exciting new feature --smartcontext, this mode provides a way of prompt context manipulation that avoids frequent context recalculation. 5 or SDXL . EvenSmarterContext) - This feature utilizes KV cache shifting to automatically remove old tokens from context and add new ones without requiring KoboldAI, on the other hand, uses "smart context" in which it will search the entire text buffer for things that it believes are related to your recently entered text. 1-70B_Q5_K_M” model with a context size of 16k and a response window of 1k tokens, I can delete even the last few replicas without having to recalculate the entire context. 30 billion * 2 bytes = 60GB. cpp\ggml Using the same model with the newest kobold. Unfortunately, because it is rebuilding the prompt frequently, it can be significantly slower than Lama CPP, but it's worth it if you are trying to get the AI KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models, inspired by the original KoboldAI. Context/Response Formatting: I don't have (I even disabled the modules and extensions I mention): Hi! I came across this comment and a similar question regarding the parameters in batched-bench and was wondering if you may be able to help me u/KerfuffleV2. ” This means a major speed increase for people like me who rely on (slow) CPU inference (or NEW FEATURE: Context Shifting (A. It only happens after there are more tokens than 2048 written from what I can tell. cpp, you must use the --ctx_size 4096 flag to enable larger contexts without seg-faulting. Notifications You must be signed in to change notification settings; Fork 299; Star 4. Context/Response Formatting: I don't have (I even disabled the modules and extensions I Closer to 60k the full-reevaluation (at a later date) took several hours. I should further add that the fundamental underpinnings of Koboldcpp, which is LLaMA. Force_Update_Build: edit. Couldn't we cache tokenization at the sentence level? Kobold. The most fair thing is total reply time but that can be affected by API hiccups. BlasBatch is 1/4 context, with max of 1024, this is to keep most people happy with 2048 context models having a BlasBatch of 512, and also 1024 is the limit. I have a laptop with 6800M Speaking of context, isn't that determined by the model itself, so you get 4K with most Llama 2 models and that's it? You aren't simply raising --contextsize beyond 4096 (with fitting --ropeconfig for appropriate scaling) unless the model itself provides a higher context?. Members Online. Enable Multiline /enable_multiline_response: Allows the bot to reply with multiple lines. cpp by ggerganov are licensed under the MIT License. And for older (GGML) models does it switch to using Smart Context or it must be manually specified After a story reaches a length that exceeds the maximum tokens, Kobold attempts to use "Smart Context" which I couldn't find any info on. 3. cpp breakout of maximum t/s for prompt and gen. Zero Install. cpp\ggml A new version of KoboldCPP supports up to 16k context. You signed out in another tab or window. The difference is always 256. K. cpp at concedo · LostRuins/koboldcpp NEW FEATURE: Context Shifting (A. cpp build and adds flexible KoboldAI API endpoints, additional format support, Stable Diffusion image generation, speech It's a single package that builds off llama. 8 T/s with a context size of 3072. Only happens with smartcontext. Q4_0_4_4), but you should consider switching to q4_0 eventually. Windows 11 RTX 3070 TI RAM 32GB 12th Gen Intel(R) Core(TM) i7-12700H, 2300 Mhz. On KoboldCPP I run kobold. 0. Reducing Prompt Processing: Try the --smartcontext flag to reduce prompt processing frequency. ggmlv3. cpp wouldn't make any sense. 0 License The amount of RAM required depends on multiple factors such as the context size, quantization type, and parameter count of the model. 6, 1. I have not tried creating a roleplaying prompt yet, but it might be possible. Once the menu appears there are 2 presets we can pick from. This is self contained distributable powered by this is an extremely interesting method of handling this. So, the current smart context AFAIK, works by looking for similar contexts and moving the context up, essentially. As for the context, I think you can just hit the Memory button right above the text entry box and supply that there. Also, the method I described before would Yes, Kobold cpp can even split a model between your GPU ram and CPU. Current Behavior. cpp and lack of updates on Kobold (i think the dev is on vacation atm ^^) I would generally advise people to try out different forks. cpp at FixSomeMess · Nexesenex/kobold. I've followed the KoboldCpp instructions on its I looked into your explanations to refresh my memory. I've already tried using smart context, but it doesn't seem to work. cpp currently does not support. cpp via ctypes bindings #315 KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models. I use the default max tokens for the model I'm using, 2048. Q3_K_M [at 8k context] Based on my personal experience, it is giving me better performance at 8k context than what I get with other back-ends at 2k context. cpp at frankenbath · Nexesenex/kobold. cpp for inference. top k is slightly more performant than other sampling methods Hi, I have a small suggestion where I'm very hopeful if you can consider adding it. cpp (a lightweight and fast solution to running 4bit quantized llama models locally). That gives you the option to put the start and end sequence in there. Once you have downloaded the file place it on your desktop, or wherever you want to store these files. xzozmh nfkvz zajjqqs kzeb lasc joy wmtdl xvlcef kvrjrl njtnkaw