metadata

base_model:
  - meta-llama/Llama-3.3-70B-Instruct
tags:
  - state-of-the-art
  - reasoning
  - chain-of-thought
  - text-generation
  - transformers
  - llama
  - instruction-tuning
license: apache-2.0
language:
  - en
datasets:
  - Daemontatox/Deepthinking-COT
  - gghfez/QwQ-LongCoT-130K-cleaned
pipeline_tag: text-generation
library_name: transformers
model-index:
  - name: Llama3.3-70B-CogniLink
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: IFEval (0-Shot)
          type: wis-k/instruction-following-eval
          split: train
          args:
            num_few_shot: 0
        metrics:
          - type: inst_level_strict_acc and prompt_level_strict_acc
            value: 69.31
            name: averaged accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: SaylorTwift/bbh
          split: test
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 52.12
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: lighteval/MATH-Hard
          split: test
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 39.58
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          split: train
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 26.06
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MuSR (0-shot)
          type: TAUR-Lab/MuSR
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 21.4
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU-PRO (5-shot)
          type: TIGER-Lab/MMLU-Pro
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 46.37
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
          name: Open LLM Leaderboard

Model Card: CogniLink - Redefining Reasoning AI

Overview

CogniLink is a state-of-the-art (SOTA) reasoning model, engineered to set new benchmarks in logical problem-solving and chain-of-thought capabilities. Leveraging the power of LLaMA 3.3 70B, CogniLink excels in multi-step reasoning, inference, and real-time decision-making across diverse domains. Whether tackling mathematical proofs, legal analyses, or dynamic real-world scenarios, CogniLink ensures clarity, precision, and scalability.

Designed for both high-performance tasks and resource-efficient environments, CogniLink represents the perfect fusion of innovation and practicality.

Key Features

Base Model: unsloth/llama-3.3-70b-instruct
Developed By: Daemontatox
License: Apache 2.0 (open and permissive)
Primary Language: English
Specialization: Multi-domain reasoning, step-by-step logic, and advanced inference.

CogniLink is optimized for tasks requiring:

Reasoning Depth: Multi-step logic with exceptional accuracy.
Chain-of-Thought (CoT): Built-in mechanisms to generate clear, stepwise reasoning paths.
Resource Efficiency: Ideal for deployment on both high-performance servers and resource-constrained devices, including edge computing platforms.

Training and Optimization

CogniLink’s fine-tuning was accelerated using Unsloth, enabling a 2x faster training pipeline. The training process was powered by Hugging Face's TRL library, ensuring seamless instruction tuning and robust adaptability across reasoning-heavy applications.

With advanced techniques like quantization-aware training and parameter-efficient fine-tuning, CogniLink is lightweight without compromising on performance, making it a top choice for edge deployment and embedded systems.

Special thanks to Modal.com for providing H100 GPUs, which enabled accelerated training and optimized performance for CogniLink. Their generous support significantly contributed to the model’s development and deployment readiness.

Applications

CogniLink is versatile and excels in various industries:

1. Education and Training

Powers AI tutors for step-by-step problem-solving in STEM education.
Supports interactive learning tools with detailed explanations.

2. Research and Academia

Assists researchers with hypothesis testing, complex analysis, and paper drafting.
Enhances productivity in tasks requiring deep logical reasoning.

3. Business Decision Support

Real-time scenario analysis for strategic decision-making.
Risk assessment tools for dynamic business environments.

4. Legal and Policy Analysis

Enables multi-step reasoning for case law interpretations and regulatory reviews.
Assists legal professionals with clear and logical argument generation.

5. Healthcare AI

Supports diagnostics and medical workflows with robust reasoning models.
Ensures accuracy in multi-step inferential tasks like patient case reviews.

Technical Specifications

Quantization: Fully compatible with 4-bit inference for efficient performance.
Latency: Optimized for real-time responses in latency-sensitive applications.
Scalability: Deployable on diverse hardware setups, from high-end GPUs to edge devices.

Why Choose CogniLink?

CogniLink isn’t just a model; it’s a reasoning companion. Its fine-tuned chain-of-thought design ensures not just answers, but rational, explainable processes, giving users the confidence and insights they need to make critical decisions.

Transparent Reasoning: Every decision is backed by a logical thought process.
Versatile Applications: From academia to business, CogniLink adapts effortlessly.
Cutting-Edge Efficiency: High performance meets cost-effectiveness.

Get Started

CogniLink is available for download and deployment. Start integrating advanced reasoning into your applications today!

For inquiries, contributions, or support, visit Unsloth GitHub.

CogniLink: Connecting Intelligence with Clarity.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here! Summarized results can be found here!

Metric	Value (%)
Average	42.47
IFEval (0-Shot)	69.31
BBH (3-Shot)	52.12
MATH Lvl 5 (4-Shot)	39.58
GPQA (0-shot)	26.06
MuSR (0-shot)	21.40
MMLU-PRO (5-shot)	46.37