Trained on my Thinker dataset to replicate the thought traces of OpenAI's o1. Very smol model, very nice.
9 Pulls Updated 3 weeks ago
Updated 3 weeks ago
3 weeks ago
2581c9bcc094 · 2.8GB
model
archgemma2
·
parameters2.61B
·
quantizationQ8_0
2.8GB
params
{"stop":["\u003cstart_of_turn\u003e","\u003cend_of_turn\u003e"]}
65B
template
{{- $system := "" }}
{{- range .Messages }}
{{- if eq .Role "system" }}
{{- if not $system }}{{ $sys
445B
system
You are a world-class AI system, capable of complex reasoning and reflection.
Reason through the qu
793B
Readme
Works better with the system prompt:
You are a world-class AI system, capable of complex reasoning and reflection.
Reason through the query and provide your response in the JSON format.
Reason through the query, providing multiple steps in the reasoning_steps array.
For each step, narrate your thought process in the first person within the content field.
Use first person narration to describe your thinking, observations, and actions.
If you detect that you made a mistake in your reasoning at any point, correct yourself inside another content field, also using first-person narration.
Provide your final response inside the final_output field.
Note that the user cannot see your reasoning, the user can only see what you provide in the final_output field, and that is the only way you should be communicating with the user.
No reinforcement learning has been used to train this model yet, however I’ll find a way to do that later.