---
base_model: Daemontatox/PathFinderAI3.0
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
- trl
license: apache-2.0
language:
- en
model-index:
- name: PathFinderAi3.0
  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: 42.71
      name: averaged accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FPathFinderAi3.0
      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: 55.54
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FPathFinderAi3.0
      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: 48.34
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FPathFinderAi3.0
      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: 21.14
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FPathFinderAi3.0
      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: 20.05
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FPathFinderAi3.0
      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: 52.86
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FPathFinderAi3.0
      name: Open LLM Leaderboard
---

![image](./image.webp)

# PathFinderAI 3.0

PathFinderAI 3.0 is a high-performance language model designed for advanced reasoning, real-time text analysis, and decision support. Fine-tuned for diverse applications, it builds upon the capabilities of Qwen2, optimized with cutting-edge tools for efficiency and performance.

## Features
- **Advanced Reasoning:** Fine-tuned for real-time problem-solving and logic-driven tasks.
- **Enhanced Performance:** Trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and the Hugging Face TRL library.
- **Multi-domain Capability:** Excels in education, research, business, legal, and healthcare applications.
- **Optimized Architecture:** Leverages Qwen2 for robust language understanding and generation.

## Training Details
- **Base Model:** Daemontatox/PathFinderAI3.0
- **Training Frameworks:** [Unsloth](https://github.com/unslothai/unsloth) and Hugging Face’s TRL library.
- **Optimization:** Quantization-aware training for faster inference and deployment on resource-constrained environments.

## Deployment
This model is ideal for deployment on both cloud platforms and edge devices, including Raspberry Pi, utilizing efficient quantization techniques.

[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

## License
The model is open-sourced under the Apache 2.0 license.

## Usage
To load the model:
```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "Daemontatox/PathFinderAI3.0"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Example usage
input_text = "What is the capital of France?"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs)
print(tokenizer.decode(outputs[0]))
```
Model Applications
PathFinderAI 3.0 is designed for:

Real-time reasoning and problem-solving
Text generation and comprehension
Legal and policy analysis
Educational tutoring
Healthcare decision support
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/Daemontatox__PathFinderAi3.0-details)!
Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=Daemontatox%2FPathFinderAi3.0&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!

|      Metric       |Value (%)|
|-------------------|--------:|
|**Average**        |    40.11|
|IFEval (0-Shot)    |    42.71|
|BBH (3-Shot)       |    55.54|
|MATH Lvl 5 (4-Shot)|    48.34|
|GPQA (0-shot)      |    21.14|
|MuSR (0-shot)      |    20.05|
|MMLU-PRO (5-shot)  |    52.86|