mirror of
https://github.com/tcsenpai/multi1.git
synced 2025-07-20 15:50:06 +00:00
clarify wording
This commit is contained in:
parent
d181f206fe
commit
35d64598d7
@ -7,7 +7,7 @@ g1 is experimental and being open sourced to help inspire the open source commun
|
||||
### Examples
|
||||
|
||||
> [!IMPORTANT]
|
||||
> g1 is not perfect, but it can perform significantly better than LLMs out-of-the-box. From initial testing, g1 accurately solves simple logic problems 60-80% of the time that usually stump LLMs. See examples below.
|
||||
> g1 is not perfect, but it can perform significantly better than LLMs out-of-the-box. From initial testing, g1 accurately solves simple logic problems 60-80% of the time that usually stump LLMs. However, accuracy has yet to be formally evaluated. See examples below.
|
||||
|
||||
|
||||
##### How many Rs are in strawberry?
|
||||
|
4
app.py
4
app.py
@ -80,10 +80,10 @@ Example of a valid JSON response:
|
||||
def main():
|
||||
st.set_page_config(page_title="g1 prototype", page_icon="🧠", layout="wide")
|
||||
|
||||
st.title("Early Prototype of g1: Using Llama-3.1 70b on Groq to create o1-like reasoning chains")
|
||||
st.title("g1: Using Llama-3.1 70b on Groq to create o1-like reasoning chains")
|
||||
|
||||
st.markdown("""
|
||||
This is an early prototype of using prompting to create o1-like reasoning chains to improve output accuracy. It is not perfect, it seems to be accurate on about 60-80% of runs on logic problems leading LLMs typically get right 0-20% of the time. It is powered by Groq so that the reasoning step is fast!
|
||||
This is an early prototype of using prompting to create o1-like reasoning chains to improve output accuracy. It is not perfect and accuracy has yet to be formally evaluated. It is powered by Groq so that the reasoning step is fast!
|
||||
|
||||
Open source [repository here](https://github.com/bklieger-groq)
|
||||
""")
|
||||
|
Loading…
x
Reference in New Issue
Block a user