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tmshapland 9 days ago

Such a fascinating read. I didn't realize how much massaging needed to be done to get the models to perform well. I just sort of assumed they worked out of the box.

acters 9 days ago | parent [-]

Personally, I think bigger companies should be more proactive and work with some of the popular inference engine software devs with getting their special snowflake LLM to work before it gets released. I guess it is all very much experimental at the end of the day. Those devs are putting in God's work for us to use on our budget friendly hardware choices.

mutkach 9 days ago | parent | next [-]

This is a good take, actually. GPT-OSS is not much of a snowflake (judging by the model's architecture card at least) but TRT-LLM treats every model like that - there is too much hardcode - which makes it very difficult to just use it out-of-the-box for the hottest SotA thing.

diggan 8 days ago | parent [-]

> GPT-OSS is not much of a snowflake

Yeah, according to the architecture it doesn't seem like a snowflake, but they also decided to invent a new prompting/conversation format (https://github.com/openai/harmony) which definitely makes it a bit of a snowflake today, can't just use what worked a couple of days ago, but everyone needs to add proper support for it.

diggan 9 days ago | parent | prev | next [-]

This is literally what they did for GPT-OSS, seems there was coordination to support it on day 1 with collaborations with OpenAI

eric-burel 9 days ago | parent | prev [-]

SMEs are starting to want local LLMs and it's a nightmare to figure what hardware would work for what models. I am asking devs in my hometown to literally visit their installs to figure combos that work.

CMCDragonkai 9 days ago | parent [-]

Are you installing them onsite?

eric-burel 8 days ago | parent [-]

Some are asking that yeah but I haven't run an install yet, I am documenting the process. This is a last resort, hosting on European cloud is more efficient but some companies don't even want to hear about cloud hosting.