corvus

joined 2 years ago
[–] [email protected] 5 points 5 days ago (2 children)

I don't know, but I really enjoyed reading his books.

[–] [email protected] 3 points 1 week ago

It gives me exactly the same message but I'm not using a VPN. When I use the external viewer option with mpv using yt-dlp I only get video without audio. I can download the video fine using yt-dlp and then watch it with mpv, but if I try to stream to mpv while downloading to watch it real-time it gives an ffmpeg error: can't recognize format... weird.

[–] [email protected] 2 points 2 weeks ago* (last edited 2 weeks ago) (1 children)

Then it's not the new C, maybe the new C++

[–] [email protected] 2 points 3 weeks ago (3 children)

Then I'll wait for Rust++

[–] [email protected] 2 points 1 month ago

I ended up buying an ASUS BT400, it works out of the box in Linux. I found it here

[–] [email protected] 1 points 1 month ago

Oh great, thanks

[–] [email protected] 2 points 1 month ago (2 children)

Yeah I tested with lower numbers and it works, I just wanted to offload the whole model thinking it will work, 2GB it's a lot. With other models it prints about 250MB when fails and if you sum up the model size it's still well below the iGPU free memory so I dont get it... anyway, I was thinking about upgrading the memory to 32GB or may be 64GB but I hesitate because with models around 7GB and CPU only I get around 5 t/s and with 14GB 2-3 t/s, so I run one of around 30GB I guess it will get around 1 t/s? My supposition is that increasing RAM doesn't increase performance per se, just let's you upload bigger models to memory, so performance is approximately linear on model size... what do you think?

[–] [email protected] 2 points 1 month ago (4 children)

I get an error when offloading the whole model to GPU

./build/bin/llama-cli -m ~/software/ai/models/deepseek-math-7b-instruct.Q8_0.gguf -n 200 -t 10 -ngl 31 -if

The relevant output is:

....

llama_model_load_from_file_impl: using device Vulkan0 (Intel(R) Iris(R) Xe Graphics (RPL-U)) - 7759 MiB free

...

print_info: file size = 6.84 GiB (8.50 BPW)

....

load_tensors: loading model tensors, this can take a while... (mmap = true) load_tensors: offloading 30 repeating layers to GPU load_tensors: offloading output layer to GPU load_tensors: offloaded 31/31 layers to GPU load_tensors: Vulkan0 model buffer size = 6577.83 MiB load_tensors: CPU_Mapped model buffer size = 425.00 MiB

.....

ggml_vulkan: Device memory allocation of size 2013265920 failed ggml_vulkan: vk::Device::allocateMemory: ErrorOutOfDeviceMemory llama_kv_cache_init: failed to allocate buffer for kv cache llama_init_from_model: llama_kv_cache_init() failed for self-attention cache common_init_from_params: failed to create context with model '~/software/ai/models/deepseek-math-7b-instruct.Q8_0.gguf' main: error: unable to load model

It seems to me that there is enough room for the model, but I don't know what "Device memory allocation of size 2013265920" means.

[–] [email protected] 2 points 1 month ago* (last edited 1 month ago) (1 children)

Is BLAS faster with CPU only than Vulkan with CPU+iGPU? After failing to make work the SYCL backend in llama.cpp apparently because of a Debian driver issue I ended up using the Vulkan backend but after many tests offloadding to the iGPU doesn't seem to make much difference.

[–] [email protected] 1 points 1 month ago* (last edited 1 month ago)

Is BLAS faster with CPU only than Vulkan with CPU+iGPU? After failing to make work the SYCL backend of llama.cpp apparently because a Debian driver issue I tried the Vulkan backend successfuly but offloading to iGPU doesn't seems to make much difference.

 

I didn't expect a 8B-F16 model with 16GB on disk could be run in my laptop with only 16GB of RAM and integrated GPU, It was painfuly slow, like 0.3 t/s, but it ran. Then I learnt that you can effectively run a model from your storage without loading into memory and checked that it was exactly the case, the memory usage kept constant at around 20% with and without running the model. The problem is that gpt4all-chat is running all the models greater than 1.5B in this way, and the difference is huge as the 1.5b model runs at 20 t/s. Even a distilled 6.7B_Q8 model with roughly 7GB on disk that has plenty of room (12GB RAM free) didn't move the memory usage and it was also very slow (3 tokens/sec). I'm pretty new to this field so I'm probably missing something basic, but I just followed the instrucctions for downloading it and compile it.

 

In Debian live images the links to download the testing branch are broken. Any alternative way to download them?

 

I bought a laptop with windows 11 instaled in its 256gb nmve ssd. I want to install linux but I want to first create an image of the ssd and store it in an external 4tb ssd with a ext4 filesystem (that I use for different backups) so in case I want to sell the laptop later I can restore windows 11 to the same ssd from the image. So what i'm planning to do is:

  • dd if=/dev/drive_device of=external_ssd/images/windows11.img

for creating the image and swapping if and of for restoring. My question is if creating the image of a drive with a windows 11 filesystem and storing it in a ext4 filesystem is possible or can have any issue. I ask this because I read that in the case of cloning the target drive will end up with the filesystem of the source drive in case they are different, which caused me some hesitation.

13
submitted 3 months ago* (last edited 3 months ago) by [email protected] to c/[email protected]
 

The situation is this:

  • I use a bluetooth dongle ASUS UB400 on my PC, bluetooth version 4.0
  • My Sony wh-1000xm5 (bluetooth version 5.3) is not detected by the PC when I scan for new bluetooth devices
  • Another Anker Soundcore Q20 headphones are detected and working fine, like the mouse and a bluetooth speaker.
  • The Sony is detected by my android smartphones and working fine
  • I switched the dongle with another one with different brand, and all the devices were detected (and work fine) with the excepcion of the Sony.
  • Using Debian 12.8 and tested with bluetoothctl

Any advice is welcome.

 

I've been using mov-cli and lobster to watch movies and series from the command line, I installed their lastest versions but they don't seem to be working anymore. I really liked their simplicity of typing the title of a movie or series and start watching on mpv. Is there any other software that works in the same way?

47
submitted 4 months ago* (last edited 4 months ago) by [email protected] to c/[email protected]
 

There is a feature in termux (android) history command which when you use !371 to execute the command 371 in the command history it prints that command in the prompt instead of executing it, then you just press enter to execute it. I found it very useful because many times I want to execute a command that is in the history but with some modification, I'm using Konsole in my desktop PC and I couldn't find an option to make such a thing. The only one I found is executing history -p !371, but that just print the command to stdout and not to the prompt itself.

EDIT: the answer is !371:p then up and the command 371 shows up in the prompt. Thanks Schizo!

 

cross-posted from: https://lemmy.ml/post/21430107

I'm having trouble to find a bluetooth dongle at least 3.0 that needs no propietary firmware. It's easy to find dongles advertised as linux compatible or users that claim that an specific brand works fine in linux, but the problem is that many of them are using propietary firmware without their users being aware because their distributions have already installed propietary drivers or firmwares, or ask users to install them and they just do it. I use debian main repository (without non-free software) in which I failed to make work a couple of linux compatible advertised dongles because debian ask me to install a propietary firmware. So if anyone knows for certain that some brand that needs no such a software in linux I'll apreciate your help.

 

I'm having trouble to find a bluetooth dongle at least 3.0 that needs no propietary firmware. It's easy to find dongles advertised as linux compatible or users that claim that an specific brand works fine in linux, but the problem is that many of them are using propietary firmware without their users being aware because their distributions have already installed propietary drivers or firmwares, or ask users to install them and they just do it. I use debian main repository (without non-free software) in which I failed to make work a couple of linux compatible advertised dongles because debian ask me to install a propietary firmware. So if anyone knows for certain that some brand that needs no such a software in linux I'll apreciate your help.

 

During the past few years I was avoiding the increasing number of products or services that required biometric verification, specially face recognition (FR). But the things are getting harder are harder in my country:

  • The largest e-commerce platform in latin america and the most used in my country requires FR to use it. It was possible to use cash if you buy from its website but since a couple of weeks it's requesting me to identify using it's app.
  • The telecoms demands FR from now on if you want a new SIM card in case you lost your phone or it's been stolen.
  • The bank is now pressing me to use their app with FR as a 2fa when using homebanking from its website, something that wasn't necessary up to some weeks ago.
  • The government is in the same direction as it's moving to digitalizing many burocratic procedures and also requires FR.

and the list is increasing quickly.

I've never used any private social networks and I've degoogled many years ago, the only non free software that I use is Whatsapp because in some countries in latin america is almost imposible not to use it, you need it even to call to the car towing service.

Anybody that is well informed knows the dangers of allowing such an amount of private information now tied to our face be available for hackers now equiped with AI, but frankly it seems a lost cause to fight against something that 99.9% of people dont worry about and give consent to do so to corporations (that sell all your data to whoever wants it) and governments (who use it as a tool of control).

I don't know, may be I'm also worring to much and it's not that serious, after all if tens of millions of people do the same the chances of being targeted by hackers is not different of being robbed in the street (at least in latin america) and with the obiquitous surveillance cameras plus the almost unavoidable need of a phone, the government probably know exactly where you are and how you look, so the information may be already available. Perhaps it's time to give up and adapt to the world we now live in.

 
 
 
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