It's a lot of "public static function do_thing_to_model(MyModel $model): MyModel {...}"
I am forever changed! It's good!
I am forever changed! It's good!
November 18, 2025 at 2:46 PM
It's a lot of "public static function do_thing_to_model(MyModel $model): MyModel {...}"
I am forever changed! It's good!
I am forever changed! It's good!
MY MODEL IS DONE MY MODEL IS DONE MYMODEL IS DONE MYMOD EL IS DONEMY MODELIS DONE MY MODEL IS DONEA AHSFASL;FHAS;LFHASL;FHAS;HA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
December 3, 2024 at 10:45 PM
MY MODEL IS DONE MY MODEL IS DONE MYMODEL IS DONE MYMOD EL IS DONEMY MODELIS DONE MY MODEL IS DONEA AHSFASL;FHAS;LFHASL;FHAS;HA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
This took me by surprise. The code generated by the @Observable macro in Xcode 26 beta 3 is noticeably different from what Xcode 16 produced.
July 22, 2025 at 7:46 AM
This took me by surprise. The code generated by the @Observable macro in Xcode 26 beta 3 is noticeably different from what Xcode 16 produced.
Formulaic is the go-to way to specify design formulas in Python, e.g. ~treatment + timepoint.
To compare sth, one needs to specify a contrast, e.g "on treatment vs baseline".
To make this easier, we developed "formulaic-contrasts":
formulaic-contrasts.readthedocs.io/en/latest/
To compare sth, one needs to specify a contrast, e.g "on treatment vs baseline".
To make this easier, we developed "formulaic-contrasts":
formulaic-contrasts.readthedocs.io/en/latest/
December 7, 2024 at 7:05 PM
Formulaic is the go-to way to specify design formulas in Python, e.g. ~treatment + timepoint.
To compare sth, one needs to specify a contrast, e.g "on treatment vs baseline".
To make this easier, we developed "formulaic-contrasts":
formulaic-contrasts.readthedocs.io/en/latest/
To compare sth, one needs to specify a contrast, e.g "on treatment vs baseline".
To make this easier, we developed "formulaic-contrasts":
formulaic-contrasts.readthedocs.io/en/latest/
Le RAG est maintenant disponible dans RamaLama. / We now have working support for RAG inside of RamaLama.
$ ramalama rag XYZ.pdf ABC.doc quay.io/NAME/myrag
$ ramalama run --rag quay.io/NAME/myrag MYMODEL
#ai #redhat
$ ramalama rag XYZ.pdf ABC.doc quay.io/NAME/myrag
$ ramalama run --rag quay.io/NAME/myrag MYMODEL
#ai #redhat
RamaLama
ramalama.ai
March 31, 2025 at 5:02 PM
Le RAG est maintenant disponible dans RamaLama. / We now have working support for RAG inside of RamaLama.
$ ramalama rag XYZ.pdf ABC.doc quay.io/NAME/myrag
$ ramalama run --rag quay.io/NAME/myrag MYMODEL
#ai #redhat
$ ramalama rag XYZ.pdf ABC.doc quay.io/NAME/myrag
$ ramalama run --rag quay.io/NAME/myrag MYMODEL
#ai #redhat
myModel
September 11, 2025 at 8:00 PM
myModel
What he said. If anything make a copy of your model with just de relevant stuff inside the migration so you don't use whatever is in app/models/
class MyMigration
class MyModel
belongs_to :my_other_model
end
def change
...
end
end
class MyMigration
class MyModel
belongs_to :my_other_model
end
def change
...
end
end
June 19, 2025 at 10:45 AM
What he said. If anything make a copy of your model with just de relevant stuff inside the migration so you don't use whatever is in app/models/
class MyMigration
class MyModel
belongs_to :my_other_model
end
def change
...
end
end
class MyMigration
class MyModel
belongs_to :my_other_model
end
def change
...
end
end
New video later today: Ride to Pacentro with myModel Y Performance Juniper #tesla #modely #teslamodely #juniper #roadtrip #pacentro #abruzzo subscribe www.youtube.com/@ciaotesla?s...
October 20, 2025 at 6:22 PM
New video later today: Ride to Pacentro with myModel Y Performance Juniper #tesla #modely #teslamodely #juniper #roadtrip #pacentro #abruzzo subscribe www.youtube.com/@ciaotesla?s...
consistency through a twice-cyclic generation process. Built on a relatively simple architecture, \mymodel achieves state-of-the-art performance on both synthetic and real-world benchmarks, and further demonstrates the effectiveness of leveraging the [6/7 of https://arxiv.org/abs/2503.08387v1]
March 12, 2025 at 6:03 AM
consistency through a twice-cyclic generation process. Built on a relatively simple architecture, \mymodel achieves state-of-the-art performance on both synthetic and real-world benchmarks, and further demonstrates the effectiveness of leveraging the [6/7 of https://arxiv.org/abs/2503.08387v1]
you should be able to just write
my_model = MyModel()
with Pipeline() as p:
p >> ['uridecodebin', {'uri':inp_file}] >> ('video/x-raw', {'format':'RGB'}) >> p.image_transform(my_model) >> 'encodebin' >> ('video/quicktime', {}) >> ['filesink', {'location':outp_file}]
my_model = MyModel()
with Pipeline() as p:
p >> ['uridecodebin', {'uri':inp_file}] >> ('video/x-raw', {'format':'RGB'}) >> p.image_transform(my_model) >> 'encodebin' >> ('video/quicktime', {}) >> ['filesink', {'location':outp_file}]
July 22, 2025 at 9:15 PM
you should be able to just write
my_model = MyModel()
with Pipeline() as p:
p >> ['uridecodebin', {'uri':inp_file}] >> ('video/x-raw', {'format':'RGB'}) >> p.image_transform(my_model) >> 'encodebin' >> ('video/quicktime', {}) >> ['filesink', {'location':outp_file}]
my_model = MyModel()
with Pipeline() as p:
p >> ['uridecodebin', {'uri':inp_file}] >> ('video/x-raw', {'format':'RGB'}) >> p.image_transform(my_model) >> 'encodebin' >> ('video/quicktime', {}) >> ['filesink', {'location':outp_file}]
Y'all saw the silhouette! Here is the art for my vtuber model! Now I have to redraw her, but like in pieces. Then just casually learn how to use Live 2D, and both vtubing software. . . 🙃🫠
🌙🌙🌙🌙🌙
#moontoxity #moontoxityart #pngtuber #vtuber #vtubermodel #mymodel #myart #myoc #streamer #artist
🌙🌙🌙🌙🌙
#moontoxity #moontoxityart #pngtuber #vtuber #vtubermodel #mymodel #myart #myoc #streamer #artist
July 20, 2025 at 8:48 PM
Y'all saw the silhouette! Here is the art for my vtuber model! Now I have to redraw her, but like in pieces. Then just casually learn how to use Live 2D, and both vtubing software. . . 🙃🫠
🌙🌙🌙🌙🌙
#moontoxity #moontoxityart #pngtuber #vtuber #vtubermodel #mymodel #myart #myoc #streamer #artist
🌙🌙🌙🌙🌙
#moontoxity #moontoxityart #pngtuber #vtuber #vtubermodel #mymodel #myart #myoc #streamer #artist
whoop whoop full provenance-preserving roundtrip serialization to JSON in #numpydantic 1.6.0.
sure you _could_ serialize a complex, nested data model with a ton of arrays in a precious high-performance data backend as a bunch of random JSON numbers and […]
[Original post on neuromatch.social]
sure you _could_ serialize a complex, nested data model with a ton of arrays in a precious high-performance data backend as a bunch of random JSON numbers and […]
[Original post on neuromatch.social]
![JSON
JSON is the ~ ♥ fun one ♥ ~
There isn’t necessarily a single optimal way to represent all possible arrays in JSON. The standard way that n-dimensional arrays are rendered in json is as a list-of-lists (or array of arrays, in JSON parlance), but that’s almost never what is desirable, especially for large arrays.
Normal Style[1]
Lists-of-lists are the standard, however, so it is the default behavior for all interfaces, and all interfaces must support it.
For our humble model:
[Python code follows, demonstrating how for a simple model with a single `array` field, each of several array formats (numpy, dask arrays, and zarr) can all be dumped to plain, identical json)]
class MyModel(BaseModel):
array: NDArray
We should get the same thing for each interface:
model = MyModel(array=[[1,2],[3,4]])
print(model.model_dump_json())
{"array":[[1,2],[3,4]]}
model = MyModel(array=da.array([[1,2],[3,4]], dtype=int))
print(model.model_dump_json())
{"array":[[1,2],[3,4]]}
model = MyModel(array=zarr.array([[1,2],[3,4]], dtype=int))
print(model.model_dump_json())
{"array":[[1,2],[3,4]]}](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:22yyehc52vyozjdxuvhlfwh6/bafkreigbzlbvydrolmdw47dvjyfghpjivxnpvoxur54rvon5jvs5z4gfem@jpeg)
![Roundtripping
To roundtrip make arrays round-trippable, use the round_trip argument to model_dump_json().
All the following should return an equivalent array from the same file/etc. as the source array when using model_validate_json() .
[More python code follows, showing how when dumping with `round_trip` additional metadata is included, in this case the `dask` array metadata about `dtype`, `chunk` shape, and the array itself (since this was an in-memory array)]
print_json(model.model_dump_json(round_trip=True))
{
'array': {
'type': 'dask',
'name': 'array-2a39187fc9fcee3f4cdbc1f2911b4b92',
'chunks': [[2], [2]],
'dtype': 'int64',
'array': [[1, 2], [3, 4]]
}
}](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:22yyehc52vyozjdxuvhlfwh6/bafkreifnhtwbx333wu5vnbikqyntv66fjchdg6or47p564sstvvahoqxlq@jpeg)
![Controlling paths
When possible, the full content of the array is omitted in favor of the path to the file that provided it.
[More python code, showing how when different array formats that are stored on disk are dumped with round_trip, the relative file path is dumped rather than the full array itself]
model = MyModel(array="data/test.avi")
print_json(model.model_dump_json(round_trip=True))
{'array': {'type': 'video', 'file': 'data/test.avi'}}
model = MyModel(array=("data/test.h5", "/data"))
print_json(model.model_dump_json(round_trip=True))
{
'array': {
'type': 'hdf5',
'file': 'data/test.h5',
'path': '/data',
'field': None
}
}](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:22yyehc52vyozjdxuvhlfwh6/bafkreicjie6zvt76atydotb6ardo2uxv5lbdiimt7xbtsltrtv75gi2ase@jpeg)
![Durable Interface Metadata
Numpydantic tries to be stable, but we’re not perfect. To preserve the full information about the interface that’s needed to load the data referred to by the value, use the mark_interface contest parameter:
[Python code, showing how the `mark_interface` parameter causes the output to gain an additional layer of metadata, with an "interface" dict defining exactly what module, class, and version were used to create it]
print_json(
model.model_dump_json(
round_trip=True,
context={"mark_interface": True}
))
{
'array': {
'interface': {
'module': 'numpydantic.interface.hdf5',
'cls': 'H5Interface',
'name': 'hdf5',
'version': '1.6.0'
},
'value': {
'type': 'hdf5',
'file': 'data/test.h5',
'path': '/data',
'field': None
}
}
}](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:22yyehc52vyozjdxuvhlfwh6/bafkreihku5algova5ccmpaeuxu67o32qbkqravciiqk22cqgns3u47ee44@jpeg)
September 24, 2024 at 1:45 AM
whoop whoop full provenance-preserving roundtrip serialization to JSON in #numpydantic 1.6.0.
sure you _could_ serialize a complex, nested data model with a ton of arrays in a precious high-performance data backend as a bunch of random JSON numbers and […]
[Original post on neuromatch.social]
sure you _could_ serialize a complex, nested data model with a ton of arrays in a precious high-performance data backend as a bunch of random JSON numbers and […]
[Original post on neuromatch.social]
May 4, 2024 at 4:42 PM
I decided it was time for a new outfit and a little bit of a change to their hair. I'm digging it.
#vtuber #vroid #kiraelric #mymodel
#vtuber #vroid #kiraelric #mymodel
January 17, 2025 at 11:26 PM
I decided it was time for a new outfit and a little bit of a change to their hair. I'm digging it.
#vtuber #vroid #kiraelric #mymodel
#vtuber #vroid #kiraelric #mymodel
Here's what the actual model definition looks like for a simple Swift model.
The @Sync property wrapper doesn't actually store anything so it should be safe to use with things like Realm's @Persisted!
Oh, and I'm calling it Anchor (cause it _sinks_ data ⚓️😉)
The @Sync property wrapper doesn't actually store anything so it should be safe to use with things like Realm's @Persisted!
Oh, and I'm calling it Anchor (cause it _sinks_ data ⚓️😉)
![An example model definition in Swift:
```swift
import Anchor
@Syncable
final class MyModel: AnchorDocument {
let id: UInt64 = UInt64.random(in: 0..<UInt64.max)
@Sync var lastWriteWins: Int = 1234
@Sync(counter: Int.self) var counter: Int = 0
@Sync(map: [String: String].self) var errorMap: [String: String] = [:]
@Sync(set: Set<String>.self) var setOfStrings: Set<String> = []
// Created by the @Syncable Macro
struct SyncMetadata: AnchorSyncMetadata { }
}
```](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:lkr4k2tscazu2d62xrwpxdup/bafkreih7hlhgjtuyvjkf4fszlbd4g76tiw4hzmfuowc4c225xefcaatine@jpeg)
August 12, 2025 at 3:55 PM
Here's what the actual model definition looks like for a simple Swift model.
The @Sync property wrapper doesn't actually store anything so it should be safe to use with things like Realm's @Persisted!
Oh, and I'm calling it Anchor (cause it _sinks_ data ⚓️😉)
The @Sync property wrapper doesn't actually store anything so it should be safe to use with things like Realm's @Persisted!
Oh, and I'm calling it Anchor (cause it _sinks_ data ⚓️😉)
Eu meio que sei como fazer isso mas queria ver se o que eu tava pensando fazia sentido.
github.com/typeorm/type...
O decorator é só uma função que retorna outra. Então vc faz o que o TS compila
const MyModel = Entity()(class MyModel {});
Com umas mudanças pra definir os campos, mas n mt complexo
github.com/typeorm/type...
O decorator é só uma função que retorna outra. Então vc faz o que o TS compila
const MyModel = Entity()(class MyModel {});
Com umas mudanças pra definir os campos, mas n mt complexo
github.com
November 26, 2024 at 1:15 PM
Eu meio que sei como fazer isso mas queria ver se o que eu tava pensando fazia sentido.
github.com/typeorm/type...
O decorator é só uma função que retorna outra. Então vc faz o que o TS compila
const MyModel = Entity()(class MyModel {});
Com umas mudanças pra definir os campos, mas n mt complexo
github.com/typeorm/type...
O decorator é só uma função que retorna outra. Então vc faz o que o TS compila
const MyModel = Entity()(class MyModel {});
Com umas mudanças pra definir os campos, mas n mt complexo
Quality of life improvement I didn't know: You can run #dbt models with all their dependencies using
`dbt run -s +mymodel` - notice the '+' in front of the model name
or run all downstream dependencies with
`dbt run -s mymodel+`
`dbt run -s +mymodel` - notice the '+' in front of the model name
or run all downstream dependencies with
`dbt run -s mymodel+`
November 13, 2024 at 3:27 PM
Quality of life improvement I didn't know: You can run #dbt models with all their dependencies using
`dbt run -s +mymodel` - notice the '+' in front of the model name
or run all downstream dependencies with
`dbt run -s mymodel+`
`dbt run -s +mymodel` - notice the '+' in front of the model name
or run all downstream dependencies with
`dbt run -s mymodel+`
:bad-valenced-emoji: testing your docs so nothing bad ever happens in them
:catnod: showing how you are a human being who can't fix every bug as soon as you see them and valuing honesty in documentation more than technical correctness when nobody has […]
[Original post on neuromatch.social]
:catnod: showing how you are a human being who can't fix every bug as soon as you see them and valuing honesty in documentation more than technical correctness when nobody has […]
[Original post on neuromatch.social]
![JSON
JSON is the ~ ♥ fun one ♥ ~
There isn’t necessarily a single optimal way to represent all possible arrays in JSON. The standard way that n-dimensional arrays are rendered in json is as a list-of-lists (or array of arrays, in JSON parlance), but that’s almost never what is desirable, especially for large arrays.
Normal style [1]
Lists-of-lists are the standard, however, so it is the default behavior for all interfaces, and all interfaces must support it.
For our humble model we should get the same thing for each interface:
[Next section is python code that doesn't fit in the alt text limit: narrative explanation: a model "MyModel" is declared with a single "array" field, which has an "NDArray" type. Several array frameworks are used to construct an instance of the model - numpy, dask, zarr, and a video, and each is serialized to json. All of them show how the JSON is identical, a trivial array of [1,2,3,4], except for the video, which repeats each number 3 times...]
(ok maybe not that last one, since the video reader still incorrectly reads grayscale videos as BGR values for now, but you get the idea)](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:22yyehc52vyozjdxuvhlfwh6/bafkreiasjgyx7a4dbgaarf77snotdg5kqgtzsyi6zjwejvz7u3mq7qajr4@jpeg)
September 21, 2024 at 8:01 AM
:bad-valenced-emoji: testing your docs so nothing bad ever happens in them
:catnod: showing how you are a human being who can't fix every bug as soon as you see them and valuing honesty in documentation more than technical correctness when nobody has […]
[Original post on neuromatch.social]
:catnod: showing how you are a human being who can't fix every bug as soon as you see them and valuing honesty in documentation more than technical correctness when nobody has […]
[Original post on neuromatch.social]
📚🐨
(1/3)
Throughout your life, you will read many books.
Some won't suit your taste, while others you'll love so much that you won't be able to stop rereading them.
They are all very different, each with its own style and its own twist.
#mypersona #oc #ocart #mymodel #art #ventart #vent
(1/3)
Throughout your life, you will read many books.
Some won't suit your taste, while others you'll love so much that you won't be able to stop rereading them.
They are all very different, each with its own style and its own twist.
#mypersona #oc #ocart #mymodel #art #ventart #vent
December 9, 2025 at 7:59 PM
I'd use a macro to make MyModel conform to ExampleObservable so I don't have to think about those ugly _example_access(...) and _example_withMutation(...) functions, of course.
July 22, 2025 at 5:16 PM
I'd use a macro to make MyModel conform to ExampleObservable so I don't have to think about those ugly _example_access(...) and _example_withMutation(...) functions, of course.
With a little more detail
![Same model example with more comments:
```swift
import Anchor
@Syncable
struct MyModel: AnchorDocument {
let id: UInt64
// Last write wins register for scalar values
@Sync var lastWriteWins = 1234
// A distributed counter, takes any `AdditiveArithmetic` value (floats, ints, custom types)
@Sync(counter: Int.self) var counter = 0
// A mergable map of keys and values. Each key acts as a last-write-wins register. Uses a
// compact tombstone representation for deleted keys.
@Sync(map: [String: String].self) var errorMap = [:]
// A set of values
@Sync(set: Set<String>.self) var setOfStrings = []
// Created by the @Syncable Macro
struct SyncMetadata: AnchorSyncMetadata { }
}
```](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:lkr4k2tscazu2d62xrwpxdup/bafkreigmh2yktsybtoz2deuftz5oweqrs5gucb36r5tcuie3kpffj3ikt4@jpeg)
August 12, 2025 at 4:00 PM
With a little more detail
I also support my friends.
For example: on Saturday, check this out if you are in the Baltimore or DMV area.
Use the promo code mymodel for a discount!
www.eventbrite.com/e/after-dark...
For example: on Saturday, check this out if you are in the Baltimore or DMV area.
Use the promo code mymodel for a discount!
www.eventbrite.com/e/after-dark...
After Dark II Photography and Live Art Exhibition
Get ready for a night of stunning photography and live art at After Dark II - it's gonna be lit!
www.eventbrite.com
November 13, 2024 at 8:42 PM
I also support my friends.
For example: on Saturday, check this out if you are in the Baltimore or DMV area.
Use the promo code mymodel for a discount!
www.eventbrite.com/e/after-dark...
For example: on Saturday, check this out if you are in the Baltimore or DMV area.
Use the promo code mymodel for a discount!
www.eventbrite.com/e/after-dark...