File size: 5,730 Bytes
55457c0 cb43062 55457c0 9f9e25a 55457c0 925fad0 cb43062 55457c0 cb43062 55457c0 cb43062 55457c0 cb43062 9f9e25a 055ba2b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 |
---
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
---
# 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|
|