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Precision Meets Efficiency: 7B Models Outperforming 70B Giants
Precision
Meets
Efficiency:
7B
Models
Outperforming
70B
Giants
We’re
fine-tuning
the
open-source
LogicNet
7B
parameter
model
to
not
just
match,
but
surpass
the
logical
reasoning
capabilities
of
70B
parameter
models.
Our Mission
Our
Mission
Build
the
world’s
largest
open-source
Logic
data
set,
called
Aristotle.
Revolutionizing Logical Reasoning
Introducing LogicNet, the pioneering framework that’s redefining the boundaries of logical reasoning in AI models.
Smarter Logic Models
Versatility: Reduced model size, lower computational overhead.
Efficiency: Effective in diverse logical reasoning tasks and domains.
Accessibility: Open-source models, accelerating research and innovation.
Our Approach
Our
Approach
These
approaches
synergize
to
create
a
powerfully
efficient
model,
excelling
in
logical
reasoning
across
various
fields
while
maintaining
a
compact
7B
parameter
size.
Synthetic Dataset Fine-Tuning
Multi-Domain Learning
LogicNet Roadmap
LogicNet
Roadmap
Advancing
Efficient
Logical
Reasoning
in
AI
Foundation and Benchmarking
Innovation in Model Architecture, Data Set Growth and Training
Scaling and Research
Specialization Platform
Inregrated with the Best Tools
Inregrated
with
the
Best
Tools
Seamlessly
connect
with
native
integrations
for
X,
Telegram,
Discord,
Github,...