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:
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
)
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
).
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.halfaker(a)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 <
isarantopoulos(a)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 <
> yoshrakpraphu(a)gmail.com> wrote:
>
>>
>> On Tue, 8 Aug 2023, 10:45 Tilman Bayer, <haebwiki(a)gmail.com> wrote:
>>
>>>
>>> Hi Chris,
>>>
>>> On Mon, Aug 7, 2023 at 11:51 AM Chris Albon <calbon(a)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/…
>>> [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 <haebwiki(a)gmail.com>
>>>> wrote:
>>>>
>>>>> On Thu, Aug 3, 2023 at 7:16 AM Chris Albon
<calbon(a)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-…
>>>>> [3]
https://phabricator.wikimedia.org/T334583 etc.
>>>>> [4]
>>>>>
https://diff.wikimedia.org/2023/06/13/mint-supporting-underserved-languages…
>>>>> 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: ml(a)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
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>>>>>> wikitech-l-leave(a)lists.wikimedia.org
>>>>>>
>>>>>>
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>>>>>
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