dots-studio/dots.mocr
Image-Text-to-Text • 3B • Updated • 497k • 166
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AlexPoto
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HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-BalancedOrganizations
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MTP in LM Studio?
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#6 opened 2 months ago
by AlexPoto
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Gemma 4 12B can now run locally on just 8GB RAM via Dynamic GGUFs.
Google's new model, Gemma 4 12B Unified supports image, audio and 256K context.
You can run and train the model via Unsloth Studio.
GGUF: unsloth/gemma-4-12b-it-GGUF
Guide: https://unsloth.ai/docs/models/gemma-4
Google's new model, Gemma 4 12B Unified supports image, audio and 256K context.
You can run and train the model via Unsloth Studio.
GGUF: unsloth/gemma-4-12b-it-GGUF
Guide: https://unsloth.ai/docs/models/gemma-4
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upvoted a collection 3 months ago
problem with tokenizer?
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#18 opened 5 months ago
by AlexPoto
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You can now run GLM-4.7, the new 355B parameter SOTA model on your local device (128GB RAM).✨
The model achieves SOTA performance on coding, agentic and chat benchmarks.
GGUF: unsloth/GLM-4.7-GGUF
Guide: https://docs.unsloth.ai/models/glm-4.7
The model achieves SOTA performance on coding, agentic and chat benchmarks.
GGUF: unsloth/GLM-4.7-GGUF
Guide: https://docs.unsloth.ai/models/glm-4.7
- 3 replies
Prompt Engineering and Context Engineering are complementary sides of the same LLM interaction process: the former crafts efficient input phrasing (like Zero-shot or Chain-of-Thought) that's cheaper and sufficient for most tasks due to minimal token usage, while the latter builds richer data environments for complex scenarios. Start with cost-effective Prompt Engineering for 80% of needs, escalating to Context Engineering only when extended knowledge or tools are required, as in your LM-Studio caching optimizations.