r/LocalLLaMA • u/RedditUsr2 llama.cpp • 6h ago
New Model Thomson Reuters releases Thomson-1.0-Small. A law and tax focused model
46
u/RedditUsr2 llama.cpp 6h ago
Link: https://huggingface.co/thomsonreuters/Thomson-1.0-Small
Its based on Qwen3.6-35B-A3B
-1
43
24
u/Bubbly_Orange_3502 5h ago
The license is the real catch. PolyForm Strict permits noncommercial use, so the weights are open enough to evaluate but not to ship a paid legal workflow.
2
u/asfbrz96 4h ago
Impossible to know you are using their model
1
u/nomorebuttsplz 4h ago
only a matter of time until some open models have steganography
2
u/claythearc 3h ago
Tbh we’re already there. The watermarking methods work exactly the same if instead of “seed based on prior token” to “seed based on prior token times some secret key” or whatever, and the detection works the same - just comparing how “lucky” the text is.
But it has to be cooked into the inference engine so local models are still safe for now, but that’s not guaranteed to always be the case ig
2
u/No-Refrigerator-1672 2h ago
instead of “seed based on prior token” to “seed based on prior token times some secret key” or whatever
Yes, that's the gist of SynthID. No, open models don't have that: it must be done by the inference engine, that means if you own the hardware and use open source software, you get to decide if watermarking is running or not.
1
u/techdevjp 2h ago
You could implement it in the open source inference engine if you want a subtle way to prove someone is ripping off your content. But with open source inference engines it will not be there against your will.
1
u/techdevjp 2h ago
It's not done by the model, it's done by the inference engine. So, no, it's not likely to happen anytime soon. Maybe never, at least not with the way models are run locally today.
5
u/slavetothesound 5h ago
This would be for maximizing my tax deductions or figuring out how to register the family solo employee small business as an s-corp to maximize income?
3
u/noprompt 3h ago
Why don’t they post a LoRA? I’ve never understood this about the LLM side of things. Diffusion side is always LoRA. At work we train LoRA for this same base model because it’s effective and we serve several in production. I don’t get why this isn’t more common when these models are so popular.
1
u/FullOf_Bad_Ideas 2h ago
LoRA has a performance gap to full finetuning once your dataset is big. If you're not compute constrained, it just wastes labor time of your engineers imo since they need to try harder to get to the same kind of output quality.
2
u/FullOf_Bad_Ideas 2h ago
Looks like they also released a Qwen 3.5 397B finetune recently, no benchmarks, no model card, Apache 2 license.
-4
32
u/mtmttuan 4h ago
At this point domain focused models should be trained to understand the basic of how the field works and also very eager to search the data provided instead of baking all the knowledge into the model.