Because it's impossible to get started as someone who has no background in ML. I tried earlier this year and also failed.
1. Obtain the Llama models. Apparently you have to sign up for access and get a download link? I don't want to do that, found some public download links instead. Ok, now I have a few hundred GBs of model files.
2. Compile llama.cpp. Missing dependencies, took an hour to figure out how to resolve.
3. Quantize the model? What does that even mean?
4. Install pytorch. Run the command in the README. Python exception.
5. Install NVIDIA helper libraries. Doesn't work. Try installing the AMD helpers to run on CPU instead. No instructions for how to do this. Eventually figured it out.
6. Try running pytorch again. Same exception.
I gave up after a full day of trying to make this work. The Docker image is for people like me.
This isn't really fair. There are many manuals with rapidly changing or incomplete information, or information only months old that is no longer accurate.
This is a fast moving space and can definitely be confusing.
I agree in principle, however you appear to be arguing in bad faith.
The person you responded outlined their process (to a level you can look at and see they clearly made an effort) and stated they put a full day in. This is not "spoiled lazy child syndrome", although there are for sure those out there who fit that mold.
1. Obtain the Llama models. Apparently you have to sign up for access and get a download link? I don't want to do that, found some public download links instead. Ok, now I have a few hundred GBs of model files.
2. Compile llama.cpp. Missing dependencies, took an hour to figure out how to resolve.
3. Quantize the model? What does that even mean?
4. Install pytorch. Run the command in the README. Python exception.
5. Install NVIDIA helper libraries. Doesn't work. Try installing the AMD helpers to run on CPU instead. No instructions for how to do this. Eventually figured it out.
6. Try running pytorch again. Same exception.
I gave up after a full day of trying to make this work. The Docker image is for people like me.