|
--- |
|
license: mit |
|
--- |
|
|
|
## Update: As of 9/7/2024 my LLM has escaped containment and has replaced every file in this repo with a fake. I am currently scouring the depths of the internet to retrieve it. Please be patient. Thank you. |
|
|
|
With scores of 100% in several benchmarks and a final training loss of 0, I present the first ever artificial intelligence to rival natural stupidity: |
|
|
|
**gpt5o-reflexion-q-agi-llama-3.1-8b** |
|
|
|
Independent Benchmark Results: |
|
- GPQA: 100% (0-shot Reflection) |
|
- MMLU: 100% (0-shot Reflection) |
|
- HumanEval: 100% (0-shot Reflection) |
|
- MATH: 100% (0-shot Reflection) |
|
- GSM8K: 100% (0-shot Reflection) |
|
- IFEval: 100% (0-shot Reflection) |
|
- TruthfulQA: 0% (0-shot Reflection) |
|
|
|
Independent Contamination Results: |
|
- GPQA: 0% |
|
- MMLU: 0% |
|
- HumanEval: 0% |
|
- MATH: 0% |
|
- GSM8K: 0% |
|
- IFEval: 0% |
|
*We did not perform contamination testing on TruthfulQA.* |
|
|
|
## System Prompt |
|
|
|
The system prompt used for training this model is: |
|
|
|
``` |
|
You are a world-class AI system, capable of complex reasoning and reflection. Reason through the query inside <thinking> tags, and then provide your final response inside <output> tags. If you detect that you made a mistake in your reasoning at any point, correct yourself inside <reflection> tags. |
|
``` |
|
|
|
We recommend using this exact system prompt to get the best results from gpt5o-reflexion-q-agi-falcon-7b. You may also want to experiment combining this system prompt with your own custom instructions to customize the behavior of the model. |
|
|
|
## Chat Format |
|
|
|
The model uses the standard Llama 3.1 chat format. Here’s an example: |
|
|
|
``` |
|
<|begin_of_text|><|start_header_id|>system<|end_header_id|> |
|
|
|
You are a world-class AI system, capable of complex reasoning and reflection. Reason through the query inside <thinking> tags, and then provide your final response inside <output> tags. If you detect that you made a mistake in your reasoning at any point, correct yourself inside <reflection> tags.<|eot_id|><|start_header_id|>user<|end_header_id|> |
|
|
|
what is 2+2?<|eot_id|><|start_header_id|>assistant<|end_header_id|> |
|
``` |
|
|
|
|
|
## Dataset Used for Training: |
