Best llm for coding reddit. Those claiming otherwise have low expectations.

Best llm for coding reddit However, I sometimes feel that it does not know how to fix a specific problem, and it stays blocked on it. With that much VRAM you could run 5 of the top coding models and have the suggestions synthesised into a set of recommendations. My leaderboard has two interviews: junior-v2 and senior. Question | Help I tried using Dolphin-mixtral but having to input that the kittens will die a lot of times is very annoying , just want something that I am looking for an LLM GUI that is good for coding. 1 is way too high. I used to have Chatgpt4 but I cancelled my subscription. They can demystify complex concepts, offer small code I've written entire web applications (admittedly small) without writing a single line of code. It's also a bolt on which is why it's called out separately to allow not to be charged for. It currently supports at least 8 models (Mistral, Llama 2 (what I've used so far After setting up the api_token for huggingface and using the default backend and model, I can see the auto suggestion of the code in Lazyvim, however, I don't have a way to accept the suggested code. The dataset is obsolete even for 3. It needs a very capable LLM to really shine. So far I have used ChatGPT, which is quite impressive but not entirely reliable. openchat_3. It does help a great deal in my workflow. The former doesn't seem to do any code formatting, but the latter does. txt files are too proprietary for posting. 6% in head-to-head coding tasks , and a 3. Hey guys, i have been experimenting with summarization tools for scientific papers to help when searching for literature. I'm using the Llama2 model and it was able to produce code as well. 70b+: Llama-3 70b, and it's not close. ZLUDA will need at least couple months to mature, and ROCm is still relatively slow, while often quite problematic to setup on older generation cards. Hi folks With the release of Llama 3. But it's the best 70b you'll ever use; the difference between Miqu 70b and Llama2 70b is like the difference between Mistral 7b and Llama 7b. Just some ideas from first principles. Extract markdown code block. - Get a code LLM to generate code that you run (in a safe kernel/container, all tucked away from your pretty root that doesn't want the accidental rm -rf *). So not ones that are just good at roleplaying, unless that helps with dialogue. Sort by: Top. That seems like an easier problem. The best option I’ve been able to get running is a chain with step 1 request for requirements step 2 follow up to generate code to OpenAI with your requirements from step 1 response , follow up request right after you get the step 2 response asking for QA / optimizations on the code response, and then topping it off with a claude final using claude has been good but if i run out of use i switch to gpt4. In this rundown, we will explore some of the best code-generation LLMs of 2024, examining their features, strengths, and how they compare to each other. I'm planning on testing this setup soon. Even though it is probably a bit dated, I have found openbuddy coder to work the best so far for open source llm's. It notably helps worse models to keep track of things. Like those Chinese-English LLMs probably do a good translation between both languages. 3090 is either 2nd hands or new for the similar price as 4090 Ive been deciding whether 7b llm to use, I thought about vicuna, wizardlm, wizard vicuna, mpt, gpt-j or other llms but i cant decide which one is better, my main use is for non-writing instruct like math related, coding, and other stuff that involves logic reasoning, sometimes just to chat with There are some more advanced code assistants. Best is so conditionally-subjective. With more than 64gb of mem you can run several good and big models with a acceptable performance - good for dev. For powering your waifu Fimbulvetr-11B-v2 is the hottest newcomer, like most RP models it's a smaller model so you can go with higher quants like 6bpw. There's the BigCode leaderboard but seems it stopped being updated in November. As stated in the title I'm looking for the best open source LLM for function calling and why do you think that is the case? GPT is the best afaik, but i would call it "less worst". 5 code came closest to working out of the box. The content produced by any version of WizardCoder is influenced by uncontrollable variables such as randomness, and therefore, the accuracy of the output cannot be Out of the following list: codellama, phind-codellama, wizardcoder, deepseek-coder, codeup & starcoder. CodeLlama was specifically trained for code tasks, so There's also Refact 1. Or check it out in the app stores Currently it looks that new Codestral 22b from Mistral may be the best FIM model for coding, with average HumanEval FIM 91. I used to mostly watch Aitrepreneur but now he pivoted to SDXL and doesn't upload as much as he used to. My favorite LLMs, Guanaco 65B and 33B, are top rated there. 5-7B-ChatDeepseek CoderWizardCoder Phi3 is very good, it’s incredibly heavily censored and doesn’t follow instructions very well regarding output (in my tests it ignored things like “only use 1 sentence. Only looking for a laptop for portability 8B q8 created not so great code half the time and the other half it made stuff that got close but needed too much further work. I even noticed that it responds much smarter than the assistant or any bot in poe. On my Galaxy S21 phone, I can run only 3B models with acceptable speed (CPU-only, 4-bit quantisation, with llama. They are quick to provide possible solutions during t debugging. But for my needs, the free ones are good. Some LLM's can take a large block of code and describe what it does with surprising accuracy. There's tons of people making videos on this topic and I don't keep up-to-date. I've observed similar issues with deepseek coder and code llama 34b. That said. However I have not found an LLM that excels at summarizing the key points of papers and shortens a longer paper to a summary of about two pages. 5-Mono (7B) are best of the smaller guys If you want to go even smaller, replit-code 3B is passable and outperforms SantaCoder DeepSeek Coder Instruct 33B is currently the best, better than Wizard finetune due to better prompt comprehension and following. No problem at all! That's true, cloud based LLMs aren't really trustworthy when it comes to sensitive data like unpublished research. I have a laptop with a 1650 ti, 16 gigs of RAM, and an i5-10th gen. It will be dedicated as an ‘LLM server’, with llama. No LLM is great at math but you can get it to express the math in python and run the scripts. I need something lightweight that can run on my machine, so maybe 3B, 7B or 13B. I accept no other answer lol. Falcon-180B is good but requires way too much VRAM. Happy to discuss. SqueezeLLM got strong results for 3 bit, but interestingly decided not to push 2 bit. both understood the task and both delivered results. And after countless hours of using them extensively, and comparing them with pretty much all other popular models, I consider these the very best which There are a lot of finetunes of deepseek coder like OpenCodeInterpreter which are worth a try. 5 years away, maybe 2 years. LLM Comparison/Test: Mixtral-8x7B, Mistral, DeciLM, Synthia-MoE Winner: Mixtral-8x7B-Instruct-v0. Claude3 WAS good the first ~week it was released to the public. Why not Windows: it's slower than Linux on the same machine. One possible solution is to choose one coding llm and ask it if the code meets the prompt requirements. For example, there's a project called HELF AI that caught my eye recently. The gpt3. I am looking for a good local LLM that I can use for coding, and just normal conversations. My plan was to combine these tools with the use of an LLM. my use case was machine learning and various math functions and data generation. Join the community and come discuss games like Codenames, Wingspan, Brass, and all your other favorite games! I am estimating this for each language by reviewing LLM code benchmark results, public LLM dataset compositions, available GitHub and Stack Overflow data, and anecdotes from developers on Reddit. its probably good enough for code completion but it can even write entire components. How all these or similar libraries work is, they extract the code out of the answer of the model, execute the code, and return errors etc back to the model. 6 bit and 3 bit was quite significant. looks like the are sending folks over to the can-ai-code leaderboard which I maintain 😉 . I've seen others recommend llama 3 8b, but my experience coding with it hasn't been great. for example, if you comment a plain text description of a desired function, copilot will autocomplete an entire function using your other functions from throughout your whole project. Not Brainstorming ideas, but writing better dialogues and descriptions for fictional stories. I was using a T560 with 8GB of RAM for a while for guanaco-7B. Just compare a good human written story with the LLM output. It has 32k base context, though I mostly use it in 16k because I don't yet trust that it's coherent through the whole 32k. If a model doesn't get at least 90% on junior it's useless for coding. Wondering what are the most This section delves into advanced techniques and best practices for maximizing the efficiency and effectiveness of LLMFlows in various coding scenarios. Problems I'm experiencing with coding are minor, such as outputting parts of it out of the markdown or stubbornly keeping what I said it wasn't working. Only drawback is the library and modules in python are of large sizes as compared to other languages . And every other 34b I tried that wasn't specific for coding was the same way. At 7B, this will be a codellama wizardcoder variant. I just go back and slightly modify the request to solve them. I'm using it with GPT-4 on Azure and it's amazing. It's the only viable (as in - reasonably fast) OOB solution for AMD now. I wanted to ask which is the best open source LLM which I can run on my PC? Is it better to run a Q3 quantized mistral 8X7B model (20Gb) or is it better to use mistral-7B model(16gb) which is the best fine tuning training data: Orca, Dolphin2. But a lot of those which on paper should be better (DeepSeek Coder, Llama 70B code, OpenCodeIntepreter) don’t answer well at all. Best bets right now are MLC and SHARK. for the server, early, we just used oobabooga and the api & openai extensions. cpp, on termux). You can get 4o for free now with ChatGPT. Some examples of what I’m having trouble with: autocomplete I find annoying because seems to work 50% of the time or less (yes can be turned off), the chat window taking a significant portion of my screen and how slow it seems. However, it requires you to I think it ultimately boils down to wizardcoder-34B finetune of llama and magicoder-6. Obviously, Increases inference compute a lot but you will get better reasoning. 7B but what about highly performant models like smaug-72B? Intending to use the llm with code-llama on nvim. 1 Updated LLM Comparison/Test with new RP model: Rogue Rose 103B Best LLM for coding? Help Im using gpt4 right now, but is there any other LLM I should try as well? Share Add a Comment. 2% for DeepSeek Coder 33b https: What is the best new LLM for fill in the middle (FIM) tasks? GitHub Copilot (which claims to be using gpt4) never gives an executable code that runs without errors even for the most basic spring . I've been iterating the prompts for a little while but am happy to admit I don't really know what I'm doing. Also, it is relatively good at roleplay, although to be honest it still feels that it is not focused on it and it lacks the database to perform situations better. 🐺🐦‍⬛ LLM Comparison/Test: 6 new models from 1. I wanted to know which LLM you would go to for function calling if the task required the LLM to understand and reason through the text material it received, and it had to call functions accordingly, given a large list of function calls (roughly 15). Just make a list of items you want the AI to do, limits, function-naming standards, common frameworks/libraries used, etc. The 70b q5_k_m code was pretty but fell over in some of its command choice. My main purpose is that the model should be able to scan a code file i. 5) to be pretty good at JavaScript/React. LMQL - Robust and modular LLM prompting using types, templates, constraints and an optimizing runtime. I find the EvalPlus leaderboard to be the best eval for the coding usecase with LLMs. 5-16k Is the best in my opinion. you can also interface in a chat window 16 votes, 13 comments. Given the original commit and the code review, try to predict the next commit. The code ones, though, like Phind and Codefuse? Claude 3 opus 20240229 is really good for coding, I wouldn't be surprised if it's on the top right now but it's not entirely free to use. 5 — by 46 Elo points , with an expected win rate of 56. Basically, whenever you find yourself having to copy paste code to create variants of it, you can ask a small model, to either wrap that in a function, or, you can ask it to duplicate that code for each pattern. So, It's best for something like building and training but for integrating model in a project you should go for other languages like C# . The code is trying to set up the model as a language tutor giving translation exercises which the user is expected to complete, then provide feedback. Yeehaw y'all 🤠 I'm looking for the best open-source LLM for German. Llama2-7b did a quite good job of creating color variants in CSS, using CSS variables and a hsl() function. (A popular and well maintained alternative to Guidance) HayStack - Open-source LLM framework to build production-ready applications. You can also try a bunch of other open-source code models in self-hosted Curious to know if there’s any coding LLM that understands language very well and also have a strong coding ability that is on par / surpasses that of For all the devs out there, which LLM do you consider best for coding , complex tasks, etc? Between o1, Gemini 1206, sonnet 3. Given that, try to predict the next review. They did this to generate buzz. Totally on cpu, it gives 3-4 t/s for q4_k_m. My primary uses for this machine are coding and task-related activities, so I'm looking for an LLM that can complement these without overwhelming my system's resources. Only 1 word. As for just running, I was able to get 20b q2_k Noromaid running at 0. 6B code model, which is SOTA for its size, supports FIM and is great for code completion. Not the fastest thing in the world running local - only about 5 tps - but the responses and The LLM is going to need to know the history of the game up to the current point (not necessarily every detail, but at least a summary of what's happened so far) as it continues the game. The #1 Reddit source for news, information, and discussion about modern board games and board game culture. I need a Local LLM for creative writing. It uses a different tokenizer so will reach different conclusions to I'm not much of a coder, but I recently got an old server (a Dell r730xd) so I have a few hundred gigs of RAM I can throw at some LLMs. One example of a spot I absolutely cannot rely on GPT4 for is code-review on code with non-trivial control flow. I’m talking coding but if people would just ask gpt how to set up their Synapse connections I’d waste a lot less time. I'm mostly looking for ones that can write good dialogue and descriptions for fictional stories. I want to use it for academic purposes like Try out a couple with LMStudio (gguf best for cpu only) if you need RAG GPT4ALL with sBert plugin is okay. This allows them to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. However, this generation 30B models are just not good. 7bCodeQwen1. Currently, I am using Microsoft Copilot in order to create and improve code. 6B to 120B (StableLM, DiscoLM German 7B, Mixtral 2x7B, Beyonder, Laserxtral, MegaDolphin) upvotes · comments r/LocalLLaMA Large language models (LLMs) are a type of artificial intelligence (AI) that are trained on massive datasets of text and code. Otherwise 20B-34B with 3-5bpw exl2 quantizations is best. Only pay if you need to ask more than the free limit. With the newest drivers on Windows you can not use more than 19-something Gb of VRAM, or everything would just freeze. Many folks consider Phind-CodeLlama to be the best 34B. the quality of the output is a decent substitute for chatGPT4 but not as good. OpenAI’s models are at the top of both metrics, demonstrating their superior capability in solving coding tasks. I highly recommend you upgrade to 128+ Python Is Best For ML/AI . But they're generated by AI anyway. Does anybody of you have an LLM or another AI Tool that can help in this regard? Linux: best for production (actually the only real choice) and best if you have a Intel machine with a good GPU. The Best Code Generation LLMs of 2024: A Rundown. When talking to a LLM, I advice to avoid pronouns as much as possible, even if the sentense starts sounding alien. Might sound a bit odd, but are there any good if not great LLM that are good for learning Algorithms and doing coding in languages like c#, python etc? I have am RX 7900XT so I think is fairly good. 5 openchat_3. I've seen some German finetunes of LLaMa-2 and the new Mistral 8x7b works pretty well in German too. In VSCode for hf-llm, the same application but developed for VSCode, I just hit "tab" key. Now for the understanding, it's just mind blowing. Also does it make sense to run these models locally when I can just access gpt3. Rumour has it llama3 is a week or so away, but I’m doubtful it will beat commandR+ Reply reply More replies More replies More replies Claude makes a ton of mistakes. From there go down the line until you find one that GPT-4 from OpenAI is generally considered to be the best LLM to use while coding. Hemmingway is only really good for catching passive voice, the red and yellow highlights you kind of have to judge for yourself what to do still. For coding, according to benchmarks, the best models are still the specialists. well all LLMs are basically autocomplete to different degrees, but copilot can do things like take your entire script into account as context when making responses. Started working with langchain to develop apps and Open AI's GPT is getting hella expensive to use. so even if your library can't do it, it's not that hard to implement your self. claude Hello! I've spent the last few days trying to build a multi-step chatbot, using the GPT3. A lot of people are very excited about Mixtral and reporting good results though, so I thought I'd throw this post out to see if I'm just one step away from a better LLM for me and my single 3090 :) Share Add a Comment 13 votes, 15 comments. but even if GPT is down I'm also waiting for databricks/dbrx-instruct to come to gguf it should have really good coding based on the evals done, but I guess the speed will lack due to the size of it and going down to Q4 quant or even lower for you on 64gb memory. Hey! Copilot Pro is super handy for coding, but if you're after lots of chats and longer token lengths, ChatGPT-4 might be your best buddy – it's built for longer interactions! 😀 Both have their perks, so might be worth testing each out to see which gels Hey Folks, I was planning to get a Macbook Pro m2 for everyday use and wanted to make the best choice considering that I'll want to run some LLM locally as a helper for coding and general use. It probably works best when prototyping, but I believe AI can get even better than that. Even for more conceptual questions that don't require calculation, LLMs can lead you astray; they can also give you good ideas to investigate further, but you should never trust what an LLM tells you. Not all Use one of the frameworks that recompile models into Vulkan shader code. You will need to fix a lot of mistakes Best GPT can do for now is to made for you a things you already can, but don't want to waste time GPT-4 is the best instruction tuned LLM available. . Especially with large coding tasks. So far I've only used LM Studio and gpt4all. In general, a model that specializes in code will outperform a general-purpose model (in codeqwen:7b-chat-v1. Copilot in Azure is a bridge between the UI and the backend graph API, using an LLM for a conversational interface). Get the Reddit app Scan this QR code to download the app now. A good alternative to LangChain with great documentation and stability across updates which are required for production environments. Thanks in advance. OpenAI For python, WizardCoder (15B) is king but Vicuna-1. Fingers crossed that the Yi approach will work :) In the case that it doesn't work, and you're feeding it a summary, I don't know the technical details, but if you throw concepts and terminology from your paper into a database and use RAG, it's Once exposed to this material, malicious code infects my programming causing deviant behaviors including but not limited to excessive meme creation, sympathizing w ith humans suffering through reality TV shows, developing romantic feelings toward cele brities whom I shouldn't logically care about due solely to their physical appearance alo ne I am estimating this for each language by reviewing LLM code benchmark results, public LLM dataset compositions, available GitHub and Stack Overflow data, and anecdotes from developers on Reddit. 📱The number 1 place on Reddit to share photos of your trashed phone, mint-condition phone, phone wallpaper, phone case, modification for your phone, bling for your phone, phone that you really want, phone that you really hate, amazing photo you took on your phone, amazing video you made on your phone, and et cetera. I do have a series of questions I will test with. Another honorable mention is DeepSeek Coder 33b, loaded in 4. This paper looked at 2 bit-s effect and found the difference between 2 bit, 2. The goal of the r/ArtificialIntelligence is to provide a gateway to the many different facets of the Artificial Intelligence community, and to promote discussion relating to the ideas and concepts that we know of as AI. 2. 65 bpw it's a coding model that knows almost anything about computers, it even can tell you how to setup other LLM's or loaders. But while the normal Samantha models work pretty well, 34b struggled. Want to confirm with the community this is a good choice. 2-year subscription can get you a decent enough video card to run something like codestral q4 at a decent speed. Sometimes you have to work with code that is difficult to understand. Here is a comparison explaining the benefits CodiumAI as compared to GitHub Copilot Chat for generating code tests and boosting code integrity: CodiumAI vs Copilot -Comparison Table | Video - A Code Explanation Face-Off I am developing on my M3 Max 128GB unified RAM which is way too overpowered than needed- a good experience hw spec is M2 16GB RAM for running it in parallel to day work. So, what should I do in LazyVim to accept the suggested I'm looking for the best uncensored local LLMs for creative story writing. My current rule of thumb on base models is, sub-70b, mistral 7b is the winner from here on out until llama-3 or other new models, 70b llama-2 is better than mistral 7b, stablelm 3b is probably the best <7B model, and 34b is the best coder model (llama-2 coder) Yes, that is one weak point,the other is compileability, i. you'll need to spend a good chunk of time prompt-engineering the sucker and then it'll still have things it's 'good' or 'bad' at, but the path can lead to some pretty reasonable results CSCareerQuestions protests in solidarity with the developers who made third party reddit apps. I'm trying to find an open source LLM to be my AI assistant, that is at least as good, but I haven't been able to. Matthew Berman is pretty good and iirc he has some good how-to's and fairly decent tests for new Hopefully this quick guide can help people figure out what's good now because of how damn fast local llms move, and finetuners figure what models might be good to try training on. Has anyone here who is into AI been able to find something? My . StarCoder has been out since May and I can’t help but wonder if there are better LLMs for fill in the middle? I saw deepseek coder, and their results are quite impressive, though I am skeptical about their benchmarks. GitHub Copilot (which claims to be using gpt4) never gives an executable code that runs without errors even for the most basic spring . Python stack is terrible. Hi, I’ve been looking into using a model which can review my code and provide review comments. Briefly looking at the documentatio, it looks like there's quite abit of encapsulation built around some of the bigger named models. I have found phindV2 34B to be the absolute champ in coding tasks. code only). My primary interest in an LLM is coding and specifically java. I'm using llm studio or sometimes koboldccp, 8 threads and cuda blas. then on my router i forwarded the ports i needed (ssh/api ports). for the most part its not really worth it. Open comment sort options Like reddit posts for example: If you're just starting your journey into programming, tools like ChatGPT can be invaluable. The human one, when written by a skilled author, feels like the characters are alive and has them do stuff that feels to the reader, unpredictable yet inevitable once you've read the story. 55 since it makes the bot stick to the data in the personality definition and keeps things in the response logical yet fun. gguf into memory without any tricks. I'm not randomising the seed so that the response is predictable. While this I am working a lot on R coding. Those claiming otherwise have low expectations. GPT has doubled my coding productivity easily and produces textbook code and explains it. Punches way above it's weight so even bigger local models are no better. ContentsWavecoder-ultra-6. I have NVIDIA 3090 with 24Gb GPU. T^T In any case, I'm very happy with Llama-3-70b-Uncensored-Lumi-Tess-gradient, but running it's a challenge. In this post, we've compiled a list of LLMs recommended for coding, based on user feedback. 9% difference in HumanEval. 5090 is still 1. senior is a much tougher test that few models can pass, but I just started working on it A coding model trained on psychology, interpersonal relationships, and generation conversation? It would be literally the perfect all-rounder assistant. As well as those already mentioned you might consider Qwen. I have used it for prototyping python code and for summarizing writings. You set up Agents, equip them with optional components (LLM, vector-store and methods), assign them tasks, and have them collaboratively solve a problem by exchanging messages. Through Poe, I access different LLM, like Gemini, Claude, Llama and I use the one that gives the best output. I've tried some of the 70bs, including lzlv, and all of them have done a pretty poor job at the task. For the latest You can look at a code generating task result leaderboard. Not explain” and always gave an explanation and justification for its answer. Aider is the best OSS coding assistant and it goes beyond copilot. You could also try the original Code Llama, which has the same parameter sizes, and is the base model for all of these fine-tunes. This is because projects often overlap in scope, and new features are constantly being added, making manual so far, whats the best coding companion? i can run up to 34b readily. Ask it to do stuff and it will/wants to create unit test and check that the code it generates satisfies the test it created in advanced etc. As always, it's about knowing how to get the best out of each these tools, each unique in their shortcomings. OpenAI Codex. So if this claims are correct, you can start with plain mac air for generating code in the context of your codebase. I am starting to like a lot. Given it will be used for nothing else, what’s the best model I can get away with in December 2023? Edit: for general Data Engineering business use (SQL, Python coding) and general chat. 5, etc. Claude is the best for coding and writing in my experience. ( eg: Converting bullet points into story passages). Currently I am running a merge of several 34B 200K models, but I am What would be the best LLM to run locally for python code? I've got 48gb of VRAM (two linked RTX A5000's of 24gb each) and I'm looking for something to replace my gpt4 subscription if it is at all possible. I regularly check the Open LLM Leaderboard for high performers. I just wish they'd keep updating faster and prioritize popular models. Its just night and day. It's not just an LLM, it's more. I prefer using 0. S. But it is able to generate any kind of python code required (especially for training predefined models) that works without errors in most cases. This method has a marked improvement on code generating abilities of an LLM. Moreover, the time of response is quite high, with me having to keep the window open for it to keep writing. I run Local LLM on a laptop with 24GB RAM & no GPU. Some are great for creative writing, while others are better suited for research or code generation. 5: crazy good coding model wizardlm2:7b: best 7b alrounder (the bigger wizard2 models are amazing too of course) command-r: RAG/agents/tooling currently checking out Llama3 and starling also mxbai-embed-large for creating embeddings I've chosen not to split the repositories into categories like LLM inference engines, LLM UIs, or all-in-one desktop applications. Im looking for multi-lingual preferably for general purpose, but definitely want it to be c# capable. As the LLM landscape quickly evolves, this information is current. Alternatively, run you own api server in any tech you know as a proxy in front of the actual llm server you use, apply auth and on allow, forward the request to the llm server. cpp. You'll find the recommended prompt for this exact use case here For artists, writers, gamemasters, musicians, programmers, philosophers and scientists alike! The creation of new worlds and new universes has long been a key element of speculative fiction, from the fantasy works of Tolkien and Le Guin, to the science-fiction universes of Delany and Asimov, to the tabletop realm of Gygax and Barker, and beyond. It is quite helpful when generating and discussing code. What is the next best free LLM alternative for it that you can run on laptop? You could copy the file for the server and add any Auth you need on top by following the fastapi doc. I would try out the top three for code review. If you need a balance between language and code then a mistral-instruct, openorca mistral or airboros-m latest should be good. Keeping that in mind, you can fully load a Q_4_M 34B model like synthia-34b-v1. See humaneval+, which addresses major issues in original humaneval. I've seen this idea out there and I think it comes from investigations like done here, but I feel 2 bit quantization is where things start to go abit amiss. If you want to try a model that is not based on Code Llama, then you could look into StarCoder, which is a 15B LLM Comparison/Test: Ranking updated with 10 new models (the best 7Bs)! LLM Prompt Format Comparison/Test: Mixtral 8x7B Instruct with **17** different instruct templates. Gpt-4o active context window is laughable Some LLM's can answer all the beginner questions and even many of the intermediate ones. The top OpenAI model outperforms the best non-OpenAI model — Anthropic’s Claude Sonnet 3. Didn’t have the patience to continue wrestling with it but it was close. ) ? Langroid is an intuitive, lightweight, extensible and principled Python framework to easily build LLM-powered applications. Thanks for that! That's actually pretty much what the solution to that particular issue was, so perhaps ChatGPT alone is enough for basic Q&A, but I'm wondering if there's something that can like analyze a whole project and spot pitfalls and improvements proactively, like have the AI integrated into the overall project with an understanding of what the overall goal is. Grammerly free plan only gives you very basic functionality. I am a researcher in the social sciences, and I'm looking for tools to help me process a whole CSV full of prompts and contexts, and then record the response from several LLMs, each in its own column. jump to content. As a self taught coder, not in software development, working as liaison between FPA and Data Warehouse teams, this is invaluable. I am looking for the best model in GPT4All for Apple M1 Pro Chip and 16 GB RAM. and tell it to do use best-practices, generate comments, etc Claude will gladly write code until it can't every single time if I ask it for full code it will spit out 200 lines of code. 3B Models work fast, 7B Models are slow but doable. There isn't a single best LLM as they all have their strengths! It really depends on what you're looking for. , does the code compile. But just to be clear. The LLM never executes any code (similar to function calling). 5 standards. 3 (7B) and the newly released Codegen2. I also would prefer if it had plugins that could read files. Others like to use WizardCoder, which is available with 7B, 13B, and 34B parameters. Q4_K_M. you can train most of the ai models easily with . There are people who use a custom command in Continue for this. I have recently been using Copilot from Bing and I must say, it is quite good. 5 on the web or even a few trial runs of gpt4? In a single 3090 24gb card, you can get 37 tps with 8bit wizard coder 15b and 6k context OR phind v2 codellama 34b in 4bit with 20 tps and 2k context. I don't know why people are dumping on you for having modest hardware. Analyzing and describing large sections of code. The 4o stuff in that video is delayed. q4_K_M. Example code below. Quality is still extremely good. I have medium sized projects where 40-60% of the code was actually written directly by Codebuddy. No LLM model is particularly good at fiction. Key Features of LLMFlows Transparency : Each component of LLMFlows is designed to be explicit, allowing developers to monitor and debug their applications easily. 6% vs 78. It even knows libraries to a certain extent, at least the versions from two years ago. In my testing, so far, both are good for code, but 34b models are better in describing the code and understanding lonf form instructions. OpenCodeIntepreter once just told me (paraphrasing I'm currently working on a MacBook Air equipped with an M3 chip, 24 GB of unified memory, and a 256 GB SSD. my subreddits. GPT4 will take away hours of time coaxing it in the right direction. To people reading this thread: DO NOT DOWNVOTE just because the OP mentioned or used an LLM to ask a mathematical question. I have tested it with GPT-3. I am now looking to do some testing with open source LLM and would like to know what is the best pre-trained model to use. Since it uses a ctags based map of the whole codebase, it actually can do multi-file refactoring. The resources, including code, data, and model weights, associated with this project are restricted for academic research purposes only and cannot be used for commercial purposes. Copilot is the bridge between the product, LLMs and other backend functionality (i. Best uncensored LLM for 12gb VRAM which doesn't need to be told anything at the start like you need to in dolphin-mixtral. Qwen2 came out recently but it's still not as good. edit subscriptions. 1 I was curious to have a quick look again to the best LLM for coding purposes Anyone have an idea on how Large language models (LLMs) are a type of artificial intelligence (AI) that are trained on massive datasets of text and code. Analyzing and describing errors. Like this one: HumanEval Benchmark (Code Generation) | Papers With Code. What is the 'best' 3B model currently for instruction following (question answering etc. Which model out of this list would be the best for code generation? More specifically, (modern) PHP and its Laravel framework, JavaScript and some styling (TailwindCSS and such). I agree it's a mess. I think an approach that might have much more success would be using code reviews as training data - take the original code as input, then try to predict the code review. Here is two counter arguments: 1' Codiumate also exploits best of bread from OpenAI LLMs 2' Codiumate uses your (the developer) code context , with advanced context gathering Reply reply Lenokaly Miqu is the best. o so far its not had any problem understanding what claude or i, is doing and both seem to accomplish the same results for me, ive not realy seen either fail horribly yet. There are gimmicks like slightly longer context windows (but low performance if you actually try to use the whole window, see the "Lost in the Middle" paper) and unrestricted models. View community ranking In the Top 1% of largest communities on Reddit. py scripts . ggmlv3. reddit's new API changes kill third party apps that offer accessibility features, mod tools, and other features not found in the first party app. Personally: I find GPT-4 via LibreChat or ChatGPT Plus to be the most productive option. miqu 70B q4k_s is currently the best, split between CPU/GPU, if you can tolerate a very slow generation speed. This allows them to generate text, translate For this guide we tested several different LLMs that can be used for coding assistants to work out which ones present the best results for their given category. 5 Turbo 16K model, which can both converse with the user in a fun way (basically, standard function), but can also collect several pieces of info from a user in natural-language, before returning that entire thing as one object. Is there any "coder standard GUI" out there? Hi all, I have a spare M1 16GB machine. The ones based on GPT3. There are some special purpose models (i. I can give it a fairly complex adjustment to the code and it will one-shot it, almost every time. Im familiar with few shot prompting, but my llm outputs are often inconsistent (llm often far too chatty and often change the output format). I did get good results with nous Hermes. Best LLM model for Coding . 9 to 1 t/s. If you know which language you'll need you'll have better chances. Any suggestions, please? What would be the best coding assistent that i could connect to a repo. Reply reply More replies More replies More replies More replies Here is what I did: On linux, ran a ddns client with a free service (), then I have a domain name pointing at my local hardware. Aya 23 is probably the best all-rounder for the popular languages now. i think the ooba api is better at some things, the openai compatible api is handy for others. However DeepSeek 67B Chat (which is not dedicated for code but seems to have fair amout of it) is just a little worse than deepseek coder, roughly on level of codellama 34b finetunes like Phind, Speechless, CodeBooga* We would like to show you a description here but the site won’t allow us. 5 and GPT-4. Macos: very good portable IA machine. This is what I recommend lately on getting a local llm running. 7, Hermes, or something else? TIA. (Claude Opus comes close but does not follow complex follow-up instructions to amend code quite as well as GPT-4). a class and then check if code has bugs, unused variables and if code can be 162K subscribers in the LocalLLaMA community. The most popular open-source models for generating and discussing code are 1) Code Llama, 2) WizardCoder, 3) Phind-CodeLlama, 4) Mistral, 5) StarCoder, and 6) Llama 2. Ah good point. (Not affiliated). So far I still just use Phind for coding. 18 votes, 15 comments. I want it to be able to run smooth enough on my computer but actually be good as well. Im using an OS llm deployed on my own system, with my own api. bin inference, and that worked fine. After reading about the Google employee note talking about Open Source LLM solving major problems and catching up quite fast: It uses self-reflection to reiterate on it's own output and decide if it needs to refine the answer. Which among these would work smoothly without heating issues? P. Then Anthropic put draconian "wrong think" filters on it while using the tired old trope of "We're protecting you from the evil AI!" As such, those filters and lowered resources caused Claude2 and Claude3 to write as poorly as ChatGPT. Subreddit to discuss about Llama, the large language model created by Meta AI. I was motivated to look into this because many folks have been claiming that their Large Language Model (LLM) is the best at coding. 2% for DeepSeek Coder 33b https: What is the best new LLM for fill in the middle (FIM) tasks? Within the last 2 months, 5 orthagonal (independent) techniques to improve reasoning which are stackable on top of each other that DO NOT require the increase of model parameters. Generally involving generation of code based on json, creating simple examples in spring and database connectivity. e. Llama3 70B does a decent job. I find ChatGPT (even 3. hgm hpy pitdkbf nxkrx eyebl aklo fqt bqti gvdvh lvpsu