Wizardlm 65b vs 30b Chose q5 If so, I’m gonna start fine-tuning against Wizard-Vicuna-30b! If not, I will probably train against it anyway, but what I’m really wondering is how likely we are to see an ecosystem pop up around certain foundation models. safetensors Press any key to continue . Reply reply tronathan • I initially focused on WizardLM-30B-Uncensored. Please see below for a LLaMA vs. Hartford 🙏), I figured that it lends itself pretty well to novel writing. 1 You can run a 65B on normal computers with KoboldCPP / llama. Perplexity is an artificial benchmark, but even 0. like 120. Eric Hartford's Wizard Vicuna 30B Uncensored GGML The difference to the existing Q8_0 is that the block size is 256. You signed out in another tab or window. 6 bit and 3 bit was quite significant. 3, surpassing This is a very good model for coding and even for general questions. WizardLM LLM Comparison. I've written it as "x Now, after screwing around with the new WizardLM-30B-Uncensored (thank you, Mr. Upload images, audio, and videos by dragging in the text input, pasting, or clicking here. When this dataset is released, a new generation of open source LLMs will be made possible and possibly to surpass GPT3. I installed it on oobabooga and run a few questions about coding, stats and music and, although it is not as detailed as GPT4, its results are impressive. Safe the most misleading things i saw in llm ai were the reports of performances of local models. cpp, or currently with text-generation-webui. If chansung made a finetuned 30B version, it'd probably be the top creative model available and a large improvement over the current GPT4 Alpaca that's out. 53. order. The new positional embedding compression in exllama solves the context problem that this model attempts to and avoids the custom code pitfall. 0 GPTQ These files are GPTQ 4bit model files for WizardLM's WizardLM 30B v1. WizardLM-2 70B reaches top-tier reasoning capabilities and is the first choice in the same size. 71. I think WizardLM-Uncensored-30B is really performant model so far. 13B FTW. The prompt format is Vicuna-1. Jun 8. This paper looked at 2 bit-s effect and found the difference between 2 bit, 2. 3, surpassing INFO:Found the following quantized model: models\TheBloke_WizardLM-Uncensored-SuperCOT-StoryTelling-30B-GPTQ\WizardLM-Uncensored-SuperCOT-Storytelling-GPTQ-4bit. My question is, how slow would it be on a cluster of m40s vs p40s, to get a reply to a question answering model of 30b or 65b? Pretty sure its a bug or unsupported, but I get 0. Pythia MPT vs 30b-q4_0 18GB View all 73 Tags Updated 13 months ago. like 70. 1. A 30B model is able to do this fairly consistently, where as every 13B model struggles to complete the task. Doesn't mean the 8_0 is better at anything else and it is certainly larger and slower than 6_K. PR & discussions documentation WizardLM-30B-Uncensored - reasoning is on the level of 65B models ! 3 #2 opened about 1 year ago by mirek190. bin. a 4 bit 30b model, though. q5_1. WizardLM-30B performance on different skills. It may or may not be the case between wildly different models or fine tunings. New In that same testing of WizardLM 30B so far, 8_0 has almost 4% more trivia knowledge than the new 6_K. It would be interesting. 65b at 2 bits per parameter vs. Trained on 1T tokens, the developers state that MPT-7B matches the performance of LLaMA while also being open source, while MPT-30B outperforms the original GPT-3. Alpaca LLaMA vs. Was the dashboard eval tests tuned to evaluate and boost the scores of llama-2? Truly baffling. over 1 year ago; WizardLM have put out their long-awaited 13B training; better than many 65B models, like solving basic physics problems correctly. What I found really interesting is that Guanaco, I believe, is the first model so far to create a new mythology without heavily borrowing from Greek WizardLM-2 8x22B is our most advanced model, and the best opensource LLM in our internal evaluation on highly complex tasks. WizardLM's WizardCoder 15B 1. Model card Files Files and versions Community 4 Train Deploy Use in Transformers. initial commit over 1 year ago; README. 8 vs. md #3. Please note that these GGMLs are not compatible with llama. 0 WizardLM-30B achieved better results than Guanaco-65B. I tested if oobabooga text gen. It tops most of the 13b models in most benchmarks I've seen it in (here's a compilation of llm benchmarks by u/YearZero). bin in conversation but for imaginative work, it seems to give up much earlier than airoboros, tending to prefer to be WizardLM has been the base for some of the best LLMs currently available. Confident-Ad-5753 The delta between 65B and 33B is not huge, but noticeable, and for the type of expense compared to what you already have invested probably worth it in your case if you're gonna be interacting with this thing a lot. As the Queen’s viceroy, you’re tasked with venturing into the unknown wilds and building new settlements inhabited by intelligent beavers, humans This model is a triple model merge of WizardLM Uncensored+CoT+Storytelling, resulting in a comprehensive boost in reasoning and story writing capabilities. I honestly haven't noticed a large quality difference between the two models, though. Guanaco LLaMA vs. 1, WizardLM-30B-V1. 7B, 13B, 30B, 66B, 175B: 7B, 13B, 70B, WizardLM-7B-V1. Cerebras-GPT LLaMA vs. (Note: MT-Bench and AlpacaEval are all self-test, will push update and OPT vs. Llama 3 LLaMA vs. However, given the models are based off of the LLaMA model Ragnarok Origin Global : แนะนำแหล่งเก็บ Lv 30-70 Wizard ไวแบบปีศาจ#ragnarokorigin -----🟡ร้านเติมเกมทุกเกม! Haven’t really tested it enough to really know. 0 GGML These files are GGML format model files for WizardLM's WizardCoder 15B 1. And then, hopefully, by 2030, there will be 40GB of Vram, and we can run the 65B-4 bit locally and the 30B-8bit locally as well. Same prompt, but the first runs entirely on an i7-13700K CPU while the second runs entirely on a 3090 Ti. 175B parameters). Gets about 10 t/s on an old CPU. Moreover, our Code LLM, WizardCoder, demonstrates exceptional performance, achieving a pass@1 score of 57. About GGUF GGUF is a new format introduced by the llama. Overview. Not using anymore. 🔥 The following figure shows that our WizardCoder-Python-34B-V1. The following figure compares WizardLM-30B and ChatGPT’s skill on Evol-Instruct testset. For me it's pretty terrible compared to WizardLM-Uncensored-30B. 13b generates text a bit slower than I can read while 7b generates text much faster than I can read it. GPTNeo LLaMA vs. WizardLM achieved significantly better results than Alpaca and Vicuna-7b on these criteria. 0 model !. GPT-J LLaMA vs. 3, surpassing WizardLM-30B-V1. Better story telling, more willing to go along with fantasy/fiction prompts, while WizardLM-7B would often say it doesn't know or that it depends or it wants clarification. Refer to the Provided Files table below to A chat between a curious user and an artificial intelligence assistant. WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions WizardLM-30B-V1. The analysis highlights how the models perform despite their differences in WizardLM-7B-V1. cpp. The models compared were ChatGPT 3. Some insist 13b parameters can be enough with great fine Is there a huge huge difference between 30b and 60/65b, especially when it comes to creative stuff? And can anyone recommend a larger model that would be best for creative pursuits, and A recent comparison of large language models, including WizardLM 7B, Alpaca 65B, Vicuna 13B, and others, showcases their performance across various tasks. It works well in a 1X12 when you want a British voice. The assistant gives helpful, detailed, and polite answers to the Initial GGML model commit over 1 year ago; WizardLM-30B-Uncensored. cpp team on August 21st 2023. Forget speed reading there. WizardLM 30B Uncensored. and it works A chat between a curious user and an artificial intelligence assistant. 13B and 30B versions of that. Llama 2. According to the paper of WizardLM, it uses a blind pairwise comparison between WizardLM and baselines on five criteria: relevance, knowledgeable, reasoning, calculation and accuracy. . I am looking For WizardLM-30B-V1. Open Pre-trained Transformer Language Models (OPT) is part of the family of open source models designed to replicate GPT-3, with similar decoder-only architecture. If we have to use 2 cards, might as well get the extra parameters and better model. I'm not sure why this dashboard has even been posted with such grievous and 🔥 The following figure shows that our WizardCoder attains the third position in this benchmark, surpassing Claude-Plus (59. All 2-6 bit dot products are implemented for this quantization type. 7B, 6. (Note: MT-Bench and AlpacaEval are all self-test, will push update and # GPT4 Alpaca LoRA 30B - 4bit GGML This is a 4-bit GGML version of the Chansung GPT4 Alpaca 30B LoRA model. alpaca polyware complied but gave me a really shitty answer - text below. Note: This performance is 100% reproducible!If you cannot reproduce it, please follow the steps in Evaluation. A recent comparison of large language models, including WizardLM 7B , Alpaca 65B , Vicuna 13B, and others, showcases their performance across various tasks. ; 🔥 Our WizardMath-70B-V1. It's interesting how this finetune has reduced some abilities compared to foundation LLaMA but increased 30b and 65b in other ways and to a similar level. WizardLM-7B-V1. For example, I am using models to generate json formatted responses to prompts. WizardLM-70B V1. FastChat LLaMA vs. 2-GGML model is what you're after, you gotta think about hardware in two ways. Contribute to Mearman/ml-helpers development by creating an account on GitHub. I tested alpaca 65b polyware-ai lora and WizardLM 30B UnCenSorEd on this prompt and WizardLM was completely censored on this one. 1. 3, surpassing Maybe I will be there now. You should train a 65b extended context lora like was just done for 13 and 30b. 6 kB. 🔥🔥🔥 [7/7/2023] The WizardLM-13B-V1. It's based on FALCON 40B, fine tuned using WizardLM. overall). 67. 72. 1 achieves 6. TheBloke/WizardLM-30B-GPTQ - would be interesting to know if the results of the non-quantized model differ. cpp and text-generation-webui. Furthermore, our WizardLM-30B model surpasses StarCoder and OpenAI's code-cushman-001. For 30B, 33B, and 34B Parameter Models For 65B and 70B Parameter Models. The GPT4-X-Alpaca 30B model, for instance, gets close to the performance of Alpaca 65B. I just tried running the 30b WizardLM model on a 6000 Ada with 48gb of RAM, and I was surprised that apparently that wasn't enough to load it (it gives me CUDA out of memory errors. (Note: MT-Bench and AlpacaEval are all self-test, will push update and The WizardLM-2–8x22B, also known as Bard, is the latest model in the WizardLM series, following the success of the previous versions WizardLM-30B and WizardLM-65B. THE FILES IN How in the world have guanaco 65b, wizardLM 30b, and wizard 13b dropped to the wayyyyy bottom of the list? These are some of the highest quality models on hugging face. Falcon LLaMA vs. Overall, WizardLM represents a significant advancement in large language models, particularly in following complex instructions and achieving impressive Was thinking of loading up: TheBloke/WizardLM-Uncensored-SuperCOT-StoryTelling-30B-GPTQ But I have seen some 65b models with 2 and 3 bit quantization. New Is there any real difference between a 13b, 30b, or 60b LLM when it comes to roleplay? Honestly, aside from some bugs and and lore mistakes here and there (like characters confusing names or misinterpreting some things), a good 13b LLM seems to be really, really solid, creative and fun. Vicuna. Run on M2 Macbook? 4 #1 opened about 1 year ago by WizardLM-7B-V1. LLaMA is not very good at quantitative reasoning, especially the smaller 7B and 13B models. For WizardLM-30B-V1. This model is license friendly, As shown in the following figure, WizardLM-30B achieved better results than Guanaco-65B. Anyone have success with those? EDIT: found out why i loads so slow. 0 at the beginning of the conversation: For WizardLM-30B-V1. The assistant gives helpful, detailed, and As shown in the following figure, WizardLM-30B achieved better results than Guanaco-65B. 3% on WizardLM Eval. Once it's finished it will say "Done". I began using runpod. 35: 75. It would be interesting to compare Q2. (assuming no issues arise) WizardLM-30B-Uncensored-GPTQ. First, for the GPTQ version, you'll want a decent GPU with at least 6GB VRAM. Text Generation PyTorch Transformers llama text-generation-inference. This model is amazing! Is there any chance that we get a 65B version of it? As shown in the following figure, WizardLM-30B achieved better results than Guanaco-65B. Results (cpu / cpu+ 3060 12gb) Alpaca-Lora-65b: 880ms / 739ms (20L) Guanaco-65B: 891ms / 737ms (20L) WizardLM-30b: 453ms / 298ms (30L) As shown in the following figure, WizardLM-30B achieved better results than Guanaco-65B. 8% of ChatGPT’s performance on average, with almost 100% (or more The LLaMA 13B model's performance is similar to GPT-3, despite being 10 times smaller (13B vs. The 65b are both 80-layer models and the 30b is a 60-layer model, for reference. 8% of ChatGPT’s WizardLM 7B vs Vicuan 13B (vs gpt-3. Really though, running gpt4-x 30B on CPU wasn't that bad for me with llama. (Note: MT-Bench and AlpacaEval are all self-test, will push update and MPT vs. I currently run 2x3090 and this is what I experience with my setup using WizardLM-30B-1. Perplexity went down a little and I saved about 2. Model card Files Files and versions Community 12 Train Deploy Use in Transformers. The new format is designed to be similar to ChatGPT, allowing for better integration with the Alpaca format and enhancing the overall user experience. It's loading lora plus q4_0 base llama model without fp16 ggml so I guess it's expected that output quality might As shown in the following figure, WizardLM-30B achieved better results than Guanaco-65B. 30b vs. It could be simply because those three other models you tried are, to put it mildly, not that great. I trained the 65b model on my texts so I can talk to myself. EOS tokens at all the right places, but more realistically it just ends up predicting the likely continuation of a chat between two participants. It breaks and starts looping quite often. The magic question for me is whether it is worth buying a new system for WizardLM 65B. Llama 2 LLaMA vs. It is not tuned for instruction following like ChatGPT, but the 65B model can follow basic instructions. With QLoRA, it becomes possible to finetune up to a 65B parameter model on a 48GB GPU without loss of performance relative to a 16-bit model. You just need 64GB of RAM. Yeah, I have yet to see tangible improvements between 30B and 65B models. by daryl149 - 13B: WizardLM ~30B: WizardLM 65B: VicUnlocked Some details on the prompting side - some of the models I wasn’t sure of whether to use Alpaca or Vicuna style prompting, so I just tried both and recorded whichever performed best. In this paper, we show an avenue for creating large amounts of instruction data . Update base_model formatting about 1 year ago; added_tokens. Even though the model is instruct-tuned, the outputs (when guided correctly) actually rival NovelAI's Euterpe model. Gemma LLaMA vs. 0 attains the second position in this benchmark, surpassing GPT4 (2023/03/15, 73. 0 achieves a substantial and comprehensive improvement on coding, mathematical reasoning and open-domain conversation capacities. 🔥 The following figure shows that our WizardCoder attains the third position in the HumanEval benchmark, surpassing Claude-Plus (59. 31%: A chat between a curious user and an artificial intelligence assistant. 1 are coming soon. To allow all output, at I tried TheBloke/WizardLM-30B-Uncensored-GPTQ and TheBloke/Wizard-Vicuna-30B-Uncensored-GPTQ, and while I did see some improvements over the popular 13b ones it's not enough imo to justify the weight and the slowness. 15. I trained this with Vicuna's FastChat, as the new data is in ShareGPT format and WizardLM team has not specified a method to train it. This is a completely different thing from the WizardLM 30B model. A chat between a curious user named [Maristic] and an AI assistant named Ava. It is my understanding that there aren't any base models of that size, and normally they jump from 13b to 70b with no in between WizardLM Uncensored SuperCOT Storytelling 30B - GGUF Model creator: YellowRoseCx; Original model: WizardLM Uncensored SuperCOT Storytelling 30B; Description This repo contains GGUF format model files for Monero's WizardLM-Uncensored-SuperCOT-Storytelling-30B. 65B version of it? #2. It was created by merging the LoRA provided in the above repo with the original Llama 30B model, producing unquantised model GPT4-Alpaca-LoRA-30B-HF. The following figure compares WizardLM-30B and ChatGPT’s Bigger model (within the same model type) is better. 1 contributor; History: 39 commits. (Note: MT-Bench and AlpacaEval are all self-test, will push update and *edit: To assess the performance of the CPU-only approach vs the usual GPU stuff, I made an orange-to-clementine comparison: I used a quantized 30B 4q model in both llama. I think 2 bit is pretty bad, but 3 bit might work depending on the use case. several independent reports of various models were saying better than gpt-3. With its improved capabilities, GPT-4 automatic evaluation, and support for multi-turn conversations with model system prompts, the WizardLM-2–8x22B is set to revolutionize the WizardLM-7B-uncensored is the best 7B model I found thus far, better than the censored wizardLM-7B which was already better than any other 7B I tested and even surpassing many 13B models. OPT. The assistant gives helpful, detailed, and polite answers to the Original model card: Monero's WizardLM-Uncensored-SuperCOT-Storytelling-30B This model is a triple model merge of WizardLM Uncensored+CoT+Storytelling, resulting in a comprehensive boost in reasoning and story writing capabilities. The files in this repo were then quantized to 4bit and 5bit for use with llama. Notably, our model exhibits a substantially smaller size compared to these models. Text Generation Transformers PyTorch llama Inference Endpoints text-generation-inference. 74 on MT-Bench Leaderboard, 86. q5_1 Env: same Performance: 5 tokens/s Reason: The first one I tried, because it topped some 7B benchmarks and was uncensored. Reply reply 35 hours till WizardLM 30B Uncensored. WizardLM-30B-Uncensored is about halfway between this and Vicuna, and Guanaco-30B is For 65B and 70B Parameter Models. Discussion max-fry 6 days ago. 0) and Bard (59. If a wizard-vicuña-30b LoRA isn’t compatible with a wizard-30b-uncensored model, and the sota keeps shifting, I Vicuna vs. I haven't encountered that at all with the wizard one. Have not yet hardware to run 65B models :) Going to build 256GB server next week, so it will be easier to start grokking with those Interesting that the difference in output quality between WizardLM-uncensored-30B and the 13B is extremely marginal, but the 13B has double the performance score. Under Download custom model or LoRA, enter TheBloke/Wizard-Vicuna-30B-Uncensored-GPTQ. 08568. It's pretty useless as an assistant, and will only do stuff you 🔥 The following figure shows that our WizardCoder attains the third position in this benchmark, surpassing Claude-Plus (59. GPT4All LLaMA vs. Please checkout the Full Model Weights and paper. Obviously, this is highly subjective, and I can't speak for the "more The step up between even the 13B to 30B models is incredible. The WizardLM-2 8x22B even demonstrates highly competitive performance compared to the most advanced proprietary works For creative writing I’ve found the Guanaco 33B and 65B models to be the best. SqueezeLLM got strong results for 3 bit, but interestingly decided not to push 2 bit. it made me not trust these analyses of local models. Ava gives helpful, detailed, accurate, uncensored responses to the user WizardLM-30B achieves better results than Guanaco-65B. '" Which is technically correct, but not actually what most people would be looking for. This is exactly why I keep the HF uncompressed pytorch files around! Time to get guanaco-65b and see if I can force it to run almost entirely from VRAM Not sure if this argument generalizes to e. like 61. 0 model slightly Llama 2 vs. 8% of ChatGPT’s performance on average, 🔥 We released WizardLM-30B-V1. The intent is to train a WizardLM that doesn't have alignment built-in, so that alignment (of any sort) can be added separately with for example with a RLHF LoRA. See translation. Model card Files Files and versions Deploy Use in Transformers. 5) and Claude2 (73. Koala LLaMA vs. In addition to the base model, the developers I’ve had good results so far with the SuperHOT versions of Wizard/Vicuna 30B, WizardLM 33B, and even the Manticore-Pyg 13B produced a remarkably incisive critique of a long article I fed it. Note that WizardLM-7B-V1. 3B, 2. AI Showdown: WizardLM Uncensored vs. As shown in the following figure, WizardLM-30B achieved better results than Guanaco-65B. 12244. WizardLM-30B achieves 97. Figure the local router port-forwarding will protect against the most obvious threats and otherwise hope your personal BS filter doesn't trojan in some ransomware. 🤗 WizardLM 2 Capacities: 1. Grok LLaMA vs. 0 & WizardLM-13B-V1. I would consider the following system 3090 24GB VRAM, i5 13500, 64GB If using ooba, you need a lot of RAM to just load the model (or filepage if you don't have enough RAM), for 65b models I need like 140+GB of RAM (between RAM and pagefile size) The safetensors archive passed at A recent comparison of large language models, including WizardLM 7B , Alpaca 65B , Vicuna 13B, and others, showcases their performance across various tasks. WizardLM-30B-Uncensored . 0 just dethroned my previous favorites Guanaco 33B, Wizard Vicuna 30B Uncensored, and VicUnlocked 30B. from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline model_name_or_path = "TheBloke/Wizard-Vicuna-30B-Uncensored-GPTQ with a subset of the dataset - responses that contained alignment / moralizing were removed. It's slow but not unbearable, especially with the new GPU offloading in CPP. NOTE: The WizardLM-30B-V1. (Note: MT-Bench and AlpacaEval are all self-test, will push update and A chat between a curious user and an artificial intelligence assistant. 2 vs. The intent is to train a WizardLM And same prompt in cyrillic too, and it seems dataset contains it enough, so it really began to give me recipe of shawarma, that contains chicken, tomato, vegetables and yoghurt. However, manually creating such instruction data is very time-consuming and labor-intensive. 55 LLama 2 70B to Q2 LLama 2 70B and see just what kind of difference that makes. like 67. 0 use different prompt with Wizard-7B-V1. The Guanaco model family outperforms all previously released models on the Vicuna benchmark. Llama 3. The analysis highlights how As shown in the following figure, WizardLM-30B achieved better results than Guanaco-65B. OPT MPT vs. I mean I should test them myself, but I lost my patience after two prompts with 65B models. Kaio Ken's SuperHOT 30b LoRA is merged on to the base model, and then 8K context can be achieved during inference by using trust_remote_code=True. I think it is a good choice to make a 2X12 sound as loud as a 4X12. gitattributes. The step up from 30B to 65B is even more noticeable. 0. 8 t/s on the new WizardLM-30B safetensor with the MPT-7B and MPT-30B are a set of models that are part of MosaicML's Foundation Series. The following figure compares WizardLM-30B WizardLM-30B-Uncensored . q4_K_M. The intent is to train a WizardLM that doesn't have 30b-fp16 65GB View all 73 Tags Updated 13 months ago. Is even better than alpaca-lora-65B. I've been using 13b 4bit and 7b 8bit mostly. maybe they are doing their benchmarks in a silly way. The WizardLM-30B model shows better results than Guanaco-65B. Update README. 5, WizardVicunaLM, VicunaLM, and WizardLM, in that order. Dolly LLaMA vs. MPT. 5 (73. In my own (very informal) testing I've found it to be a better all-rounder and make less mistakes than my previous favorites, which include WizardLM-7B-V1. 30B q4 is the very limit already as text generation can barely keep up with my reading speed, and that’s if I give myself copious amount of time to read. Click Download. WizardLM-Uncensored-SuperCOT-StoryTelling-30b. 0) trained with 250k evolved instructions (from ShareGPT). 0: 🤗 HF Link: 7. Checkout the Demo_30B, Demo_30B_bak and the Just curious, was the original WizardLM 65b a flop? I'm also pretty impressed with wizardlm-30b-uncensored. wizardlm-30b wrong output #211. 32% on AlpacaEval Leaderboard, and 99. My test VM was configured as: Ubuntu 22 + WizardLM-30B-V1. q4_0. WizardLM 30B V1. 5 especially with training it on other bases such as MPT, Falcon, RedPajama, and OpenLlama, at sizes up to 40b and 65b, which the community will be The Wizard is a very efficient (Loud) British voiced speaker with a voice that falls between a Greenback and a Vintage 30. json. 8% of ChatGPT’s performance on average, with almost 100% (or more My Al-Pacino-30B-based assistant replied, "His last words were, 'Time to die. with a subset of the dataset - responses that contained alignment / moralizing were removed. 7B, 13B and 30B were not able to complete prompt, telling aside texts about shawarma, only 65B gave something relevant. Model: WizardLM-7B-uncensored. I tried several different prompt variations, but found a longer prompt to generally give the best results. Reply reply Duval79 Guanaco vs. 0, the Prompt should be as following: "A chat between a curious user and an artificial intelligence assistant. According to the authors, Vicuna achieves more than 90% of ChatGPT's quality in user preference tests, while vastly outperforming Alpaca. bin on CPU only. 4GB so the next best would be vicuna 13B. . It does a better job of following the prompt than straight Guanaco, in my experience. Guanaco. Gemma 2 LLaMA vs. We would like to show you a description here but the site won’t allow us. For GPU inference and GPTQ formats, you'll want a top-shelf GPU with at least 40GB The following figure compares WizardLM-30B and ChatGPT’s skill on Evol-Instruct testset. If it's a corporate pc, CYA & get your resume together. arxiv: 2308. License: other. 1 in this unit is significant to generation quality. Training large language models (LLMs) with open-domain instruction following data brings colossal success. Get started with WizardLM. Hello, Reddit! I'm back with another AI showdown, this time featuring two 30B models: Guanaco-33B-GGML WizardLM-30B-GGML I've tested both models using the Llama Precise Preset in the Text Generation Web UI, both are q4_0. You switched accounts on another tab or window. If it does & it's a person pc then wipe (more likely buy) a new machine, lose some stuff, and move on. When I responded, "That's technically correct, though the sentence before that is usually what people remember," it replied, "Yes, his actual last line was, 'All those moments will be lost in time, like tears in rain. 98c19ab about 1 year ago. When you step up to the big models like 65B and 70B models (), you need some serious hardware. 8 pass@1: Non-commercial: WizardLM-13B-V1. Text Generation PyTorch Transformers llama. Guanaco 65b is the only (finished) finetune other than ancient Alpaca Loras for 65b so it At present, our core contributors are preparing the 65B version and we expect to empower WizardLM with the ability to perform instruction evolution itself, aiming to evolve your specific data at a low cost. ggml. 0 with Other LLMs. Model card Files Files and versions Community 6 New discussion New pull request. The questions presented here are not from rigorous tests, but rather, I asked a few questions and requested GPT-4 to score them. When pairing with other speakers, it is important to pay attention to the sensitivity rating of 102. 5). My M2 base mac can't run anything other than 7B models 4bit or less quantized Llama 3 vs. ML Model Helper Utilities. You should try WizardLM uncensored 13b, and GPT4-x-Vicuna 13b. To download from a specific branch, enter for example TheBloke/Wizard-Vicuna-30B-Uncensored-GPTQ:main; see Provided Files above for the list of branches for each option. Yes, I really loved WizardLM, however I didn't find an issue with personality cohearence but I had optimized and really ground-down my Character's Token count. Llama 3 is Meta AI's open source LLM available for both research and commercial use cases (assuming you have less than 700 million monthly active users). MT-Bench (Figure-1) The WizardLM-2 8x22B even demonstrates highly competitive performance compared to the most advanced proprietary works such as GPT-4-Trubo and Glaude-3. Gpt4-x-vicuna, GPT-4 as the judge (test in comments) Against the Storm is a roguelite city builder set in a fantasy world where it never stops raining. 🔥 We released 30B version of WizardLM (WizardLM-30B-V1. So we really went straight from waiting for Vicuna 30B to waiting for WizardLM 13B huh Dany0 • Fingers crossed Reply reply More replies [deleted] • WizardLM-65B when 😭😭 Reply reply More replies. 13 months ago WizardLM is a 70B parameter model based on Llama 2 trained by WizardLM. A chat between a curious user and an artificial intelligence assistant. If gpt4 can be trimmed down somehow just a little, I think that would be the current best under 65B. WizardLM-30B achieves better results than Guanaco-65B. I'm referring to Laptops by the way. 44. But to answer your question, yes, much better Comparing WizardCoder-Python-34B-V1. arxiv: 2306. 🔥 The following figure shows that our WizardCoder attains the third position in this benchmark, surpassing Claude-Plus (59. To allow all output, at the end of your prompt add ### Certainly! Spaces using Monero/WizardLM-Uncensored-SuperCOT-StoryTelling-30b 26. So I expect an uncensored Wizard-Vicuna-7B to WizardLM-7B-V1. Open Z000000 opened this issue Sep 24, 2023 · 2 comments Open wizardlm-30b wrong output #211. 🔥 [08/11/2023] We release WizardMath Models. The analysis highlights how the models perform despite their differences in parameter count. The gpt4-x-alpaca 30B 4 bit is just a little too large at 24. I get 3-4 q3_k_m was better than q4_0 when testing ausboss/llama-30b-supercot. Reload to refresh your session. all three were much better than WizardLM (censored and uncensored variants), Vicuna (censored and uncensored variants), GPT4All-13B My short experiences with Guac 33b vs WizLM 30b highlight some interesting differences. It tells incoherent stories. ) I added a second 6000 Ada, and checked auto-devices in Oobabooga, but it still only tries to load into one GPU and I still get the CUDA errors. 5 tk/s, which is just about usable. Released alongside Koala, Vicuna is one of many descendants of the Meta LLaMA model trained on dialogue data collected from the ShareGPT website. Safe. Reply reply 65b: Somewhere around 40GB minimum Good rule of thumb is to look at the size of the . The model used in the example below is the WizardLM model, with 70b parameters, which is This is WizardLM trained with a subset of the dataset - responses that contained alignment / moralizing were removed. Moreover, humans may struggle to produce high-complexity instructions. The assistant gives helpful, detailed, and polite answers to the Look how rich and good looking is the webpage generated by wizardlm-30b comparing to robin-65B-v2. ggmlv3. md. Mistral LLaMA Introducing the newest WizardLM-70B V1. 0-4bit and Guanaco-65B-4-bit. Copy link Z000000 commented Sep 24, 2023. In fact, no base 7b model approaches usability. TheBloke Update base_model formatting. 2). As of NOTE: The WizardLM-30B-V1. 21 Bytes. Resources. (Note: MT-Bench and AlpacaEval are all self-test, will push update and WizardLM-30B-Uncensored-GGML. 09583. 8% of ChatGPT’s performance on the Evol-Instruct testset from GPT-4's view. Orca MPT vs. like 12. 5 GB of VRAM. Z000000 opened this issue Sep 24, 2023 · 2 comments Comments. 1, and WizardLM-65B-V1. Llama 2 is Meta AI's open source LLM available for both research and commercial use cases (assuming you're not one of the top consumer companies in the world). 01: 37. If the 7B WizardLM-13B-V1. by max-fry - opened 6 days ago. MPT-7B and MPT-30B are a set of models that are part of MosaicML's Foundation Series. Running more threads than physical cores slows it down, and offloading some layers to gpu speeds it up a bit. Those are by far the best 13b we have available, at least in my own testing, and the testing of several others I Monero's WizardLM-Uncensored-SuperCOT-Storytelling-30B GGML The difference to the existing Q8_0 is that the block size is 256. When you step up to the big models like 65B and 70B models You signed in with another tab or window. Do you notice a difference between 30B and 65B? At the moment the 30B model is running on my system (3060 8GB VRAM, i511400F, 32 GB RAM DDR4) with 1. 48 kB. The model used in the example below is the WizardLM model, with 70b parameters, which is The WizardLM-2–8x22B, also known as Bard, is the latest model in the WizardLM series, following the success of the previous versions WizardLM-30B and WizardLM-65B. safetensors file, and add 25% for context and processing. Thireus. 13B, 33B, 65B: 7B, 30B: MPT vs. Wizardlm-30b also is giving much better answers at any topic. ehartford/WizardLM_evol_instruct_V2_196k_unfiltered_merged_split. It follows few shot instructions better and is zippy enough for my taste. 0 (Demo_30B, Demo_30B_bak) and WizardLM-13B-V1. Notably, our model exhibits a substantially smaller size compared to these models. The model will start downloading. However this 13B model is still new and interesting, because whereas the 7B was trained on a 70k dataset, this was trained Monero's WizardLM Uncensored SuperCOT Storytelling 30B fp16 This is fp16 pytorch format model files for Monero's WizardLM Uncensored SuperCOT Storytelling 30B merged with Kaio Ken's SuperHOT 8K. The assistant gives helpful, detailed, and polite answers to the user's questions. Initial GPTQ model commit. At present, our core contributors are preparing the 65B version and we expect to empower WizardLM with the ability to perform instruction evolution itself, aiming to evolve your specific data at a low cost. g. q5_0. The Manticore-13B-Chat-Pyg-Guanaco is also very good. EOS issue can be fixed by making sure the chat Not like you'll be waiting hours for a response, but I haven't used it much as a result. io to run 30B & 65B instead, which has been a great way to test run them before investing in new hardware. In wsl2 the io speed Hey everyone, I'm back with another exciting showdown! This time, we're putting GPT4-x-vicuna-13B-GPTQ against WizardLM-13B-Uncensored-4bit-128g, as they've both been garnering quite a bit of attention lately. I was making reasoning tests and I am really impressed. Other repositories available 4-bit GPTQ models for GPU inference; 4-bit, 5-bit and 8-bit GGML models for CPU(+GPU) inference; WizardLM-13B-V1. Solved this one - only 65b solving it properly (only gpt4-alpaca-lora_mlp-65B actually) solve this equation and explain each step 2Y-12=-16 Original model card: Eric Hartford's Wizardlm 30B Uncensored This is WizardLM trained with a subset of the dataset - responses that contained alignment / moralizing were removed. It has since been superseded by models such as LLaMA, GPT-J, and Pythia. Till now, only Vicuna1. 0 at the beginning of the conversation:. FLAN-T5 LLaMA vs. Prompting You should prompt the LoRA the same way you would prompt Alpaca or Alpacino. Text Generation Transformers PyTorch llama text-generation-inference. so you're likely thinking of WizardLM-13B-Uncensored. The result indicates that WizardLM-30B achieves 97. I think it will also help a lot when we get a proper finetuned 65b model like vicuña/wizardlm, since 65b has a lot of untapped potential right now. 0: 🤗 HF Link: 6. Based on the WizardLM/WizardLM_evol_instruct_V2_196k dataset I filtered it to remove refusals, avoidance, bias. FLAN-UL2 LLaMA vs. It is the result of quantising to 4bit using GPTQ-for-LLaMa. Is even better than alpaca-lora In my experiments, WizardLM-30B and another model is so incredibly far ahead of the rest. Edit Preview. arxiv: 2304. Phi MPT vs. 0), ChatGPT-3. act. 1 and WizardLM are the best 2 for me. Meanwhile, i have updated to the new oobabooga, and downloaded the the Vic unlocked 30B GGML model, it is working but after few messages it starts to be extremely slow, when i checked the task manager, i noticed that my GPU is not loaded at all, only ram and CPU are used during the text generation , i have this flages # CMD_FLAGS = '--pre_layer 60 --cpu WizardLM's WizardLM 30B v1. It doesn't get talked about very much in this subreddit so I wanted to bring some more attention to Nous Hermes. 60/65b - does it make a big difference? As shown in the following figure, WizardLM-30B achieved better results than Guanaco-65B. 5 or even gpt-4 and it was never true. I Based on the WizardLM/WizardLM_evol_instruct_V2_196k dataset I filtered it to remove refusals, avoidance, bias. Hell, no 65b model approaches usability either (they're even worse than 30b models which are themselves only marginally better than 13b models, go figure). 5-turbo) Comparison. Easily beat all 7B , 13B and 30b models. wqqxde vkigu pjtih reelw xfqnf gfa rsqdg agby tebd dtwz