Hi Aaron! Thanks for following up. The API is almost compatible with what ORES currently does, but there are limitations (like the max number of revisions in a batch etc..). The API clearly states when something is not supported, so you can check its compatibility now making some requests to:
https://ores-legacy.wikimedia.org If you open a task with a list of systems that you need to migrate we can definitely take a look and help. So far the traffic being served by ORES has been reduced to few clients, and all of them don't run with recognizable UAs (see https://meta.wikimedia.org/wiki/User-Agent_policy) so we'll try our best to support them. The migration to Lift Wing has been widely publicized, a lot of documentation is available to migrate. We'd suggest trying Lift Wing for your systems instead (see https://wikitech.wikimedia.org/wiki/Machine_Learning/LiftWing/Usage). The Machine Learning plan is to eventually deprecate ores-legacy too, to maintain only one system (namely Lift Wing). There is no final date yet, we'll try to reach out to all remaining users first, so if you plan to keep using ores-legacy please follow up with us first :) Thanks! Luca (on behalf of the ML Team) On Fri, Sep 22, 2023 at 5:10 PM Aaron Halfaker <aaron.halfa...@gmail.com> wrote: > Does the new ores-legacy support the same feature set. E.g. features > output, injection, and threshold optimizations. Or is it just prediction? > This will affect some of the systems I need to migrate. > > On Fri, Sep 22, 2023, 06:21 Ilias Sarantopoulos < > isarantopou...@wikimedia.org> wrote: > >> Hello! >> >> >> As a next step in the deprecation process of ORES >> https://wikitech.wikimedia.org/wiki/ORES the Machine Learning team will >> switch the backend of ores.wikimedia.org to ores-legacy, a k8s >> application meant to provide a compatibility layer between ORES and Lift >> Wing so users that have not yet migrated to Lift Wing will be >> transparently migrated. Ores-legacy is an application that has the same API >> as ORES but in the background makes requests to Lift Wing, allowing us to >> decommission the ORES servers until all clients have moved. >> >> This change is planned to take place on Monday 25th of September. If you >> have a client/application that is still using ORES we expect that this >> switch is going to be transparent for you. >> >> However keep in mind that ores-legacy is not a 100% replacement for ORES >> as some old and unused features are no longer supported. >> >> If you see anything out of the ordinary, feel free to contact the Machine >> Learning team: >> >> IRC libera: #wikimedia-ml >> >> Phabricator: Machine-Learning-team tag >> >> Thank you! >> >> >> On Wed, Aug 9, 2023 at 1:22 PM Chaloemphon Praphuchakang < >> yoshrakpra...@gmail.com> wrote: >> >>> >>> On Tue, 8 Aug 2023, 10:45 Tilman Bayer, <haebw...@gmail.com> wrote: >>> >>>> >>>> Hi Chris, >>>> >>>> On Mon, Aug 7, 2023 at 11:51 AM Chris Albon <cal...@wikimedia.org> >>>> wrote: >>>> >>>>> Hi Tilman, >>>>> >>>>> Most of the work is still very experimental. We have hosted a few LLMs >>>>> on Lift Wing already (StarCoder for example) but they were just running on >>>>> CPU, far too slow for real use cases. But it proves that we can easily >>>>> host >>>>> LLMs on Lift Wing. We have been pretty quiet about it while we focus on >>>>> the >>>>> ORES migration, but it is our next big project. More soon hopefully! >>>>> >>>> Understood. Looking forward to learning more later! >>>> >>>> >>>>> Where we are now is that we have budget for a big GPU purchase (~10-20 >>>>> GPUs depending on cost), the question we will try to answer after the ORES >>>>> migration is complete is: what GPUs should we purchase? We are trying to >>>>> balance our strong preference to stay open source (i.e. AMD mROC) in a >>>>> world dominated by a single closed source vendor (i.e. Nvidia). In >>>>> addition, do we go for a few expensive GPUs better suited to LLMs (A1000, >>>>> H100, etc) or a mix of big and small? We will need to figure out all this. >>>>> >>>> I see. On that matter, what do you folks make of the recent >>>> announcements of AMD's partnerships with Hugging Face and Pytorch[5]? >>>> (which, I understand, came after the ML team had already launched the >>>> aforementioned new AMD explorations) >>>> >>>> "Open-source AI: AMD looks to Hugging Face and Meta spinoff PyTorch to >>>> take on Nvidia [...] >>>> Both partnerships involve AMD’s ROCm AI software stack, the company’s >>>> answer to Nvidia’s proprietary CUDA platform and application-programming >>>> interface. AMD called ROCm an open and portable AI system with >>>> out-of-the-box support that can port to existing AI models. [...B]oth AMD >>>> and Hugging Face are dedicating engineering resources to each other and >>>> sharing data to ensure that the constantly updated AI models from Hugging >>>> Face, which might not otherwise run well on AMD hardware, would be >>>> “guaranteed” to work on hardware like the MI300X. [...] AMD said PyTorch >>>> will fully upstream the ROCm software stack and “provide immediate ‘day >>>> zero’ support for PyTorch 2.0 with ROCm release 5.4.2 on all AMD Instinct >>>> accelerators,” which is meant to appeal to those customers looking to >>>> switch from Nvidia’s software ecosystem." >>>> >>>> >>>> In their own announcement, Hugging Face offered further details, >>>> including a pretty impressive list of models to be supported:[6] >>>> >>>> >>>> "We intend to support state-of-the-art transformer architectures for >>>> natural language processing, computer vision, and speech, such as BERT, >>>> DistilBERT, ROBERTA, Vision Transformer, CLIP, and Wav2Vec2. Of course, >>>> generative AI models will be available too (e.g., GPT2, GPT-NeoX, T5, OPT, >>>> LLaMA), including our own BLOOM and StarCoder models. Lastly, we will also >>>> support more traditional computer vision models, like ResNet and ResNext, >>>> and deep learning recommendation models, a first for us. [..] We'll do our >>>> best to test and validate these models for PyTorch, TensorFlow, and ONNX >>>> Runtime for the above platforms. [...] We will integrate the AMD ROCm SDK >>>> seamlessly in our open-source libraries, starting with the transformers >>>> library." >>>> >>>> >>>> Do you think this may promise too much, or could it point to a possible >>>> solution of the Foundation's conundrum? >>>> In any case, this seems to be an interesting moment where many in AI >>>> are trying to move away from Nvidia's proprietary CUDA platform. Most of >>>> them probably more for financial and availability reasons though, given the >>>> current GPU shortages[7] (which the ML team is undoubtedly aware of >>>> already; mentioning this as context for others on this list. See also >>>> Marketwatch's remarks about current margins[5]). >>>> >>>> Regards, Tilman >>>> >>>> >>>> [5] >>>> https://archive.ph/2023.06.15-173527/https://www.marketwatch.com/amp/story/open-source-ai-amd-looks-to-hugging-face-and-meta-spinoff-pytorch-to-take-on-nvidia-e4738f87 >>>> [6] https://huggingface.co/blog/huggingface-and-amd >>>> [7] See e.g. >>>> https://gpus.llm-utils.org/nvidia-h100-gpus-supply-and-demand/ (avoid >>>> playing the song though. Don't say I didn't warn you) >>>> >>>> >>>>> I wouldn't characterize WMF's Language Team using CPU as because of >>>>> AMD, rather at the time we didn't have the budget for GPUs so Lift Wing >>>>> didn't have any. Since then we have moved two GPUs onto Lift Wing for >>>>> testing but they are pretty old (2017ish). Once we make the big GPU >>>>> purchase Lift Wing will gain a lot of functionality for LLM and similar >>>>> models. >>>>> >>>>> Chris >>>>> >>>>> On Sun, Aug 6, 2023 at 9:57 PM Tilman Bayer <haebw...@gmail.com> >>>>> wrote: >>>>> >>>>>> On Thu, Aug 3, 2023 at 7:16 AM Chris Albon <cal...@wikimedia.org> >>>>>> wrote: >>>>>> >>>>>>> Hi everybody, >>>>>>> >>>>>>> TL;DR We would like users of ORES models to migrate to our new open >>>>>>> source ML infrastructure, Lift Wing, within the next five months. We are >>>>>>> available to help you do that, from advice to making code commits. It is >>>>>>> important to note: All ML models currently accessible on ORES are also >>>>>>> currently accessible on Lift Wing. >>>>>>> >>>>>>> As part of the Machine Learning Modernization Project ( >>>>>>> https://www.mediawiki.org/wiki/Machine_Learning/Modernization), the >>>>>>> Machine Learning team has deployed a Wikimedia’s new machine learning >>>>>>> inference infrastructure, called Lift Wing ( >>>>>>> https://wikitech.wikimedia.org/wiki/Machine_Learning/LiftWing). >>>>>>> Lift Wing brings a lot of new features such as support for GPU-based >>>>>>> models, open source LLM hosting, auto-scaling, stability, and ability to >>>>>>> host a larger number of models. >>>>>>> >>>>>> >>>>>> This sounds quite exciting! What's the best place to read up on that >>>>>> planned support for GPU-based models and open source LLMs? (I also saw in >>>>>> the recent NYT article[1] that the team is "in the process of adapting >>>>>> A.I. >>>>>> models that are 'off the shelf; — essentially models that have been made >>>>>> available by researchers for anyone to freely customize — so that >>>>>> Wikipedia’s editors can use them for their work.") >>>>>> >>>>>> I'm aware of the history[2] of not being able to use NVIDIA GPUs due >>>>>> to their CUDA drivers being proprietary. It was mentioned recently in the >>>>>> Wikimedia AI Telegram group that this is still a serious limitation, >>>>>> despite some new explorations with AMD GPUs[3] - to the point that e.g. >>>>>> the >>>>>> WMF's Language team has resorted to using models without GPU support (CPU >>>>>> only).[4] >>>>>> It sounds like there is reasonable hope that this situation could >>>>>> change fairly soon? Would it also mean both at the same time, i.e. open >>>>>> source LLMs running with GPU support (considering that at least some >>>>>> well-known ones appear to require torch.cuda.is_available() == True for >>>>>> that)? >>>>>> >>>>>> Regards, Tilman >>>>>> >>>>>> [1] >>>>>> https://www.nytimes.com/2023/07/18/magazine/wikipedia-ai-chatgpt.html >>>>>> [2] >>>>>> https://techblog.wikimedia.org/2020/04/06/saying-no-to-proprietary-code-in-production-is-hard-work-the-gpu-chapter/ >>>>>> [3] https://phabricator.wikimedia.org/T334583 etc. >>>>>> [4] >>>>>> https://diff.wikimedia.org/2023/06/13/mint-supporting-underserved-languages-with-open-machine-translation/ >>>>>> or https://thottingal.in/blog/2023/07/21/wikiqa/ (experimental but, >>>>>> I understand, written to be deployable on WMF infrastructure) >>>>>> >>>>>> >>>>>>> >>>>>>> With the creation of Lift Wing, the team is turning its attention to >>>>>>> deprecating the current machine learning infrastructure, ORES. ORES >>>>>>> served >>>>>>> us really well over the years, it was a successful project but it came >>>>>>> before radical changes in technology like Docker, Kubernetes and more >>>>>>> recently MLOps. The servers that run ORES are at the end of their >>>>>>> planned >>>>>>> lifespan and so to save cost we are going to shut them down in early >>>>>>> 2024. >>>>>>> >>>>>>> We have outlined a deprecation path on Wikitech ( >>>>>>> https://wikitech.wikimedia.org/wiki/ORES), please read the page if >>>>>>> you are a maintainer of a tool or code that uses the ORES endpoint >>>>>>> https://ores.wikimedia.org/). If you have any doubt or if you need >>>>>>> assistance in migrating to Lift Wing, feel free to contact the ML team >>>>>>> via: >>>>>>> >>>>>>> - Email: m...@wikimedia.org >>>>>>> - Phabricator: #Machine-Learning-Team tag >>>>>>> - IRC (Libera): #wikimedia-ml >>>>>>> >>>>>>> The Machine Learning team is available to help projects migrate, >>>>>>> from offering advice to making code commits. We want to make this as >>>>>>> easy >>>>>>> as possible for folks. >>>>>>> >>>>>>> High Level timeline: >>>>>>> >>>>>>> **By September 30th 2023: *Infrastructure powering the ORES API >>>>>>> endpoint will be migrated from ORES to Lift Wing. For users, the API >>>>>>> endpoint will remain the same, and most users won’t notice any change. >>>>>>> Rather just the backend services powering the endpoint will change. >>>>>>> >>>>>>> Details: We'd like to add a DNS CNAME that points ores.wikimedia.org >>>>>>> to ores-legacy.wikimedia.org, a new endpoint that offers a almost >>>>>>> complete replacement of the ORES API calling Lift Wing behind the >>>>>>> scenes. >>>>>>> In an ideal world we'd migrate all tools to Lift Wing before >>>>>>> decommissioning the infrastructure behind ores.wikimedia.org, but >>>>>>> it turned out to be really challenging so to avoid disrupting users we >>>>>>> chose to implement a transition layer/API. >>>>>>> >>>>>>> To summarize, if you don't have time to migrate before September to >>>>>>> Lift Wing, your code/tool should work just fine on >>>>>>> ores-legacy.wikimedia.org and you'll not have to change a line in >>>>>>> your code thanks to the DNS CNAME. The ores-legacy endpoint is not a >>>>>>> 100% >>>>>>> replacement for ores, we removed some very old and not used features, >>>>>>> so we >>>>>>> highly recommend at least test the new endpoint for your use case to >>>>>>> avoid >>>>>>> surprises when we'll make the switch. In case you find anything weird, >>>>>>> please report it to us using the aforementioned channels. >>>>>>> >>>>>>> **September to January: *We will be reaching out to every user of >>>>>>> ORES we can identify and working with them to make the migration >>>>>>> process as >>>>>>> easy as possible. >>>>>>> >>>>>>> **By January 2024: *If all goes well, we would like zero traffic on >>>>>>> the ORES API endpoint so we can turn off the ores-legacy API. >>>>>>> >>>>>>> If you want more information about Lift Wing, please check >>>>>>> https://wikitech.wikimedia.org/wiki/Machine_Learning/LiftWing >>>>>>> >>>>>>> Thanks in advance for the patience and the help! >>>>>>> >>>>>>> Regards, >>>>>>> >>>>>>> The Machine Learning Team >>>>>>> _______________________________________________ >>>>>>> Wikitech-l mailing list -- wikitech-l@lists.wikimedia.org >>>>>>> To unsubscribe send an email to wikitech-l-le...@lists.wikimedia.org >>>>>>> >>>>>>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >>>>>> >>>>>> _______________________________________________ >>>>>> Wikitech-l mailing list -- wikitech-l@lists.wikimedia.org >>>>>> To unsubscribe send an email to wikitech-l-le...@lists.wikimedia.org >>>>>> >>>>>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >>>>> >>>>> _______________________________________________ >>>>> Wikitech-l mailing list -- wikitech-l@lists.wikimedia.org >>>>> To unsubscribe send an email to wikitech-l-le...@lists.wikimedia.org >>>>> >>>>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >>>> >>>> _______________________________________________ >>>> Wikitech-l mailing list -- wikitech-l@lists.wikimedia.org >>>> To unsubscribe send an email to wikitech-l-le...@lists.wikimedia.org >>>> >>>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >>> >>> _______________________________________________ >>> Wikitech-l mailing list -- wikitech-l@lists.wikimedia.org >>> To unsubscribe send an email to wikitech-l-le...@lists.wikimedia.org >>> >>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >> >> _______________________________________________ >> Wikitech-l mailing list -- wikitech-l@lists.wikimedia.org >> To unsubscribe send an email to wikitech-l-le...@lists.wikimedia.org >> >> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ > > _______________________________________________ > Wikitech-l mailing list -- wikitech-l@lists.wikimedia.org > To unsubscribe send an email to wikitech-l-le...@lists.wikimedia.org > https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/
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