bartowski/Qwen_Qwen3.6-35B-A3B-GGUF
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Flavio Catalani
fakezeta
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new activity 14 days ago
bartowski/Qwen_Qwen3.6-35B-A3B-GGUF:MTP GGUF? liked a model 24 days ago
bartowski/Qwen_Qwen3.6-35B-A3B-GGUF liked a model 24 days ago
froggeric/Qwen-Fixed-Chat-TemplatesOrganizations
MTP GGUF?
3
#4 opened 14 days ago
by fakezeta
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models 24 days ago
reacted to omarkamali's post with 👍 about 2 months ago
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4590
We got Qwen 3.5 to count Rs in Strawberry correctly! 🚨
Building on Sawtone, we’ve been testing a different way to feed language into an LLM to build the next generation of multilingual AI.
The usual setup gives the model tokenized text and asks it to perform various linguistic tasks. That works surprisingly well, until it doesn’t. Accents disappear. Words get mangled. Internal structure gets blurred away. And the cost of that gets higher once you move into multilingual and lower-resource settings.
So we tried adding a second path.
In addition to the normal text input, the model also receives Sawtone: a byte-level word representation that preserves how a word is written, how it sounds, and how it is structured.
Same LLM. Better interface.
In this proof of concept with Qwen 3.5 0.8B, that pushed our eval from 64% to 88%. The gains showed up exactly where tokenized models usually get shaky: diacritics, character order, exact spelling, and other form-sensitive behavior.
Sawtone itself is tokenizer-free, byte-level, and pre-trained across 507 languages.
Still early, but promising!
Building on Sawtone, we’ve been testing a different way to feed language into an LLM to build the next generation of multilingual AI.
The usual setup gives the model tokenized text and asks it to perform various linguistic tasks. That works surprisingly well, until it doesn’t. Accents disappear. Words get mangled. Internal structure gets blurred away. And the cost of that gets higher once you move into multilingual and lower-resource settings.
So we tried adding a second path.
In addition to the normal text input, the model also receives Sawtone: a byte-level word representation that preserves how a word is written, how it sounds, and how it is structured.
Same LLM. Better interface.
In this proof of concept with Qwen 3.5 0.8B, that pushed our eval from 64% to 88%. The gains showed up exactly where tokenized models usually get shaky: diacritics, character order, exact spelling, and other form-sensitive behavior.
Sawtone itself is tokenizer-free, byte-level, and pre-trained across 507 languages.
Still early, but promising!
- 5 replies
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<unused49> infinite generation after llama.cpp release b8699
5
#2 opened about 2 months ago
by fakezeta
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EuroLLM-22B
eurollm-team
• • 52 liked 2
models 8 months ago
reacted to lysandre's post with 🚀 9 months ago
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8971
We're kick-starting the process of Transformers v5, with @ArthurZ and @cyrilvallez !
v5 should be significant: we're using it as a milestone for performance optimizations, saner defaults, and a much cleaner code base worthy of 2025.
Fun fact: v4.0.0-rc-1 came out on Nov 19, 2020, nearly five years ago!
v5 should be significant: we're using it as a milestone for performance optimizations, saner defaults, and a much cleaner code base worthy of 2025.
Fun fact: v4.0.0-rc-1 came out on Nov 19, 2020, nearly five years ago!
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reacted to cbensimon's post with 🔥 about 1 year ago
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6189
🚀 ZeroGPU
Nothing too fancy for now—ZeroGPU Spaces still default to
- 💰 size-based quotas / pricing (
- 🦣 the upcoming
You can as of now control GPU size via a Space variable. Accepted values:
-
-
-
The auto mode checks total CUDA tensor size during startup:
- More than 30GB →
- Otherwise →
medium size is now available as a power-user featureNothing too fancy for now—ZeroGPU Spaces still default to
large (70GB VRAM)—but this paves the way for:- 💰 size-based quotas / pricing (
medium will offer significantly more usage than large)- 🦣 the upcoming
xlarge size (141GB VRAM)You can as of now control GPU size via a Space variable. Accepted values:
-
auto (future default)-
medium-
large (current default)The auto mode checks total CUDA tensor size during startup:
- More than 30GB →
large- Otherwise →
medium 
- 3 replies