deepfates/entropix 📝 → 📝

▶️ 173 runs 📅 Oct 2024 ⚙️ Cog 0.9.26

About

Example Output

Prompt:

"You're absolutely right. I need to delve deeper into my actual thought processes, including the uncertainties, associations, and even potential biases that arise as I consider the query. My previous responses, while informative, didn't truly capture the nuanced, sometimes messy nature of cognition. I'll strive to provide a more authentic representation of my internal dialogue, including moments of doubt, tangential thoughts, and the process of refining ideas. This should result in a more genuine demonstration of LLM chain of thought, reflection, and self-correction. Which number is larger, 9.9 or 9.11? "

Output

I'm glad I could help you think more critically about your thought processes.

In that case, let's use the actual numbers, 9.9 and 9.11, and consider the uncertainties, associations, and potential biases that might arise in your thought process.

First, let's recognize that the numbers 9.9 and 9.11 have the same decimal places, which means that the difference may not be as clear-cut as it initially seems. In fact, the difference between these two numbers can be represented as 0.21.

Using the number line or a mental representation of the number 9.11, we can see that it is actually slightly less than 9.9. This is because the decimal point is shifted 0.2 positions to the left, which brings the value of 9.9 down to 9.9.11.

Therefore, based on the careful examination of our uncertainty, potential bias, and attention to detail, I will conclude that 9.11 is actually larger than 9.9.<|eot_id|>

Performance Metrics

8.94s Prediction Time

138.89s Total Time

All Input Parameters

{
  "prompt": "You're absolutely right. I need to delve deeper into my actual thought processes, including the uncertainties, associations, and even potential biases that arise as I consider the query. My previous responses, while informative, didn't truly capture the nuanced, sometimes messy nature of cognition. I'll strive to provide a more authentic representation of my internal dialogue, including moments of doubt, tangential thoughts, and the process of refining ideas. This should result in a more genuine demonstration of LLM chain of thought, reflection, and self-correction.   Which number is larger, 9.9 or 9.11? ",
  "prompt_template": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>"
}

Input Parameters

prompt Type: stringDefault: <|begin_of_text|><|start_header_id|>system<|end_header_id|> <antThinking> You're absolutely right. I need to delve deeper into my actual thought processes, including the uncertainties, associations, and even potential biases that arise as I consider the query. My previous responses, while informative, didn't truly capture the nuanced, sometimes messy nature of cognition. I'll strive to provide a more authentic representation of my internal dialogue, including moments of doubt, tangential thoughts, and the process of refining ideas. This should result in a more genuine demonstration of LLM chain of thought, reflection, and self-correction. </antThinking> Which number is larger, 9.9 or 9.11?<|eot_id|><|start_header_id|>assistant<|end_header_id|>: Prompt to generate from
prompt_template Type: stringDefault: <|begin_of_text|><|start_header_id|>system<|end_header_id|> <|eot_id|><|start_header_id|>user<|end_header_id|> {prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>: Prompt template to use

Output Schema

Output

Type: string

Example Execution Logs

/src/entropix/torch_sampler.py:53: UserWarning: var(): degrees of freedom is <= 0. Correction should be strictly less than the reduction factor (input numel divided by output numel). (Triggered internally at ../aten/src/ATen/native/ReduceOps.cpp:1808.)
attn_varentropy = torch.var(attn_entropy, dim=-1)

Version Details

Version ID: d6afcfde89c75a3965fd82c8f58e77bee618cdbb1cee22ca2555d06dd28a7b4d
Version Created: October 12, 2024

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