This is again a big win on the red team at least for me. They developed a “fully open” 3B parameters model family trained from scratch on AMD Instinct™ MI300X GPUs.
AMD is excited to announce Instella, a family of fully open state-of-the-art 3-billion-parameter language models (LMs) […]. Instella models outperform existing fully open models of similar sizes and achieve competitive performance compared to state-of-the-art open-weight models such as Llama-3.2-3B, Gemma-2-2B, and Qwen-2.5-3B […].
As shown in this image (https://rocm.blogs.amd.com/_images/scaling_perf_instruct.png) this model outperforms current other “fully open” models, coming next to open weight only models.
A step further, thank you AMD.
PS : not doing AMD propaganda but thanks them to help and contribute to the Open Source World.
I don’t know why open sourcing malicious software is worthy of praise but okay.
I’ll bite, what is malicious about this?
What’s malicious about AI and LLMs? Have you been living under a rock?
At best it is useless, and at worst it is detrimental to society.
I disagree, LLMs have been very helpful for me and I do not see how an open source AI model trained with open source datasets is detrimental to society.
I don’t know what to say other than pull your head outta the sand.
No you.
Explain your exact reasons for thinking it’s malicious. There’s a lot of FUD surrounding “AI,” a lot of which come from unrealistic marketing BS and poor choices by C-suite types that have nothing to do with the technology itself. If you can describe your concerns, maybe I or others can help clarify things.
These models are trained on human creations with the express intent to drive out those same human creators. There is no social safety net available so those creators can maintain a reasonable living standard without selling their art. It won’t even work–the models aren’t good enough to replace these jobs, but they’re good enough to fool the C-suite into thinking they can–but they’ll do lots of damage in the attempt.
The issues are primarily social, not technical. In a society that judges itself on how well it takes care of the needs of everyone, I would have far less of an issue with it.
The issues are primarily social, not technical.
Right, and having a FOSS alternative is certainly a good thing.
I think it’s important to separate opposition to AI policy from a specific implementation. If your concerns are related to the social impact of a given technology, that is where the opposition should go, not toward the technology itself.
That said, this is largely similar to opposition to other types of technological change. Every time a significant change in technology comes about, there is a significant impact to jobs. The printing press destroyed the livelihood of scribes, but it made books dramatically cheaper, which created new jobs for typesetters, booksellers, etc. The automobile dramatically cut back jobs like farriers, stable hands, etc, but created new jobs for drivers, mechanics, etc. I’m sure each of those large shifts in technology also had an overreaction by business owners as they adjusted to the new normal. It certainly sucks for those impacted, but it tends to benefit those who can quickly adapt and make use of the new technology.
So I totally understand the hesitation around AI, especially given the overreaction by C-suites in gutting their workforce based on the promises made by AI marketing teams. However, that has nothing to do with the technology, but the social issues around the technology. Instead of hating AI in general, redirect that anger onto the actual problems:
- poor social safety net
- expensive education
- lack of consequences for false marketing
- lack of consequences for C-suite mistakes
Hating on a FOSS model just because it’s related to an industry that is seeing abuse is the wrong approach.
So in a nutshell, it’s malicious because you said so
Ok gotcha Mr/Ms/Mrs TechnoBigot
Yes, that’s totally what I said.
Something we all agree on
3B
That’s one more than 2B so she must be really hot!
/nierjokes
AMD knew what they were doing.
That’s a real stretch. 3B is basically stating the size of the model, not the name of the model.
Are you calling her fat?
Can’t judge you for wanting to **** her or whatever, just don’t ask her for freebies. She won’t care if you are a human at that point.
I know it’s not the point of the article but man that ai generated image looks bad. Like who approved that?
Oh yeah you’re right :-)
Properly open source.
The model, the weighting, the dataset, etc. every part of this seems to be open. One of the very few models that comply with the Open Software Initiative’s definition of open source AI.
Look at the picture in my post.
There was others open models but they were very below the “fake” open source models like Gemma or Llama, but Instella is almost to the same level, great improvement
Every AI model outperforms every other model in the same weight class when you cherry pick the metrics… Although it’s always good to have more to choose from
I’ve shared this AI because it’s one of the best fully open source AI
Nice and open source . Similar performance to Qwen 2.5.
(also … https://www.tomsguide.com/ai/i-tested-deepseek-vs-qwen-2-5-with-7-prompts-heres-the-winner ← tested DeepSeek vs Qwen 2.5 … )
→ Qwen 2.5 is better than DeepSeek.
So, looks good.Dont know if this test in a good representation of the two AI, but in this case it seems pretty promising, the only thing missing is a high parameters model
Help me understand how this is Open Source? Perhaps I’m missing something, but this is Source Available.
Instead of the traditional open models (like llama, qwen, gemma…) that are only open weight, this model says that it has :
Fully open-source release of model weights, training hyperparameters, datasets, and code
Making it different from other big tech “open” models. Tough it exists other “fully open” models like GPT neo, and more
The source code on these models is almost too boring to care about. Training data and weights is what really matters.
And we are still waiting on the day when these models can actually be run on AMD GPUs without jumping through hoops.
In other words, waiting for the day when antitrust law is properly applied against Nvidia’s monopolization of CUDA.
That is a improvement, if the model is properly trained with rocm it should be able to run on amd GPU easier
I’ll be bookmarking the website & thank you
Nice. Where do I find the memory requirements? I have an older 6GB GPU so I’ve been able to play around with some models in the past.
No direct answer here, but my tests with models from HuggingFace measured about 1.25GB of VRAM per 1B parameters.
Your GPU should be fine if you want to play around.
LMstudio usually lists the memory recommendations for the model.
Following this page it should be enough based on the requirements of qwen2.5-3B https://qwen-ai.com/requirements/
It’s about AI.
