huihui-ai/DeepSeek-V3-abliterated
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FiditeNemini
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#1 opened 11 days ago
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luigi12345's
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22 days ago
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✅BEST DEBUG PROMPT
Language: Any. 🌀Project Type: Any
Language: Any. 🌀Project Type: Any
What prompt if sent to you will make you detect and fix all the code crashing issues in the COMPLETE codebase so I don't have to ask you to fix again and again ?
Step 1. Gimme such prompt
Step 2 Follow it yourself quietly and COMPLETELY
Step3: State that if you are asked again about finding fatal bugs and logic issues and inconsistencies in the current codebase you would not be able to find more. (You cannot lie, so you must make all the code adjustments necessary prior to such statement).
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2104
This recent paper points to an explanation for the unreasonable effectiveness of Frankenmerges:
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth
Approach (2502.05171)
Specifically, the duplication of layers in Frankenmerges serves a purpose similar to what occurs in their recurrent-depth architecture. Successful frankenmerges that operate without additional fine-tuning are able to recover or "heal" from any damage due to abrupt transitions between layer blocks. Operational replicated layer blocks can provide functional benefits grounded in latent reasoning. Frankenmerges can also result in hybrid reasoning, by splicing together the latent reasoning of different models.
Back in April 2024, I was able to duplicate a few layers in the Llama 3 8B model, turning it into a 9B model, without harming benchmarks significantly, despite any transition damage.
grimjim/llama-3-experiment-v1-9B
My informal experimentation suggested that latent reasoning circuits could occupy continguous stacks of 2-4 layers, though the result was highly sensitive to the choice of transition location between layers.
Specifically, the duplication of layers in Frankenmerges serves a purpose similar to what occurs in their recurrent-depth architecture. Successful frankenmerges that operate without additional fine-tuning are able to recover or "heal" from any damage due to abrupt transitions between layer blocks. Operational replicated layer blocks can provide functional benefits grounded in latent reasoning. Frankenmerges can also result in hybrid reasoning, by splicing together the latent reasoning of different models.
Back in April 2024, I was able to duplicate a few layers in the Llama 3 8B model, turning it into a 9B model, without harming benchmarks significantly, despite any transition damage.
grimjim/llama-3-experiment-v1-9B
My informal experimentation suggested that latent reasoning circuits could occupy continguous stacks of 2-4 layers, though the result was highly sensitive to the choice of transition location between layers.
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I’ve simplified things for the AI OS community!
Check out Qwen-2.5-14B-DeepSeek-R1-1M! This one's a cool blend of the latest Qwen 2.5 with 14 billion parameters and has a massive 1 million token context window. It also comes with the DeepSeek R1 version of the Qwen 2.5 14B base model.
Enjoy! 🚀
mkurman/Qwen2.5-14B-DeepSeek-R1-1M
Check out Qwen-2.5-14B-DeepSeek-R1-1M! This one's a cool blend of the latest Qwen 2.5 with 14 billion parameters and has a massive 1 million token context window. It also comes with the DeepSeek R1 version of the Qwen 2.5 14B base model.
Enjoy! 🚀
mkurman/Qwen2.5-14B-DeepSeek-R1-1M
1M token context version is out
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#2 opened about 1 month ago
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#1 opened about 1 month ago
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🐋DeepSeek 🐋 is the real OpenAI 😯
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