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PathFinderAI2.0 by Daemontatox

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  4bit   Autotrain compatible   Conversational   En   Endpoints compatible   Quantized   Qwen2   Region:us   Safetensors   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/Daemontatox/PathFinderAI2.0 

PathFinderAI2.0 Benchmarks

MMLU Pro: 50.52
GPQA: 6.94
MUSR: 10.96
BBH: 52.96
IFEval: 45.41 vs 88 (so35)-48.4%
MATH Lvl 5: 26.13
LLME Score: 0.33686
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
PathFinderAI2.0 (Daemontatox/PathFinderAI2.0)

PathFinderAI2.0 Parameters and Internals

LLM NamePathFinderAI2.0
Repository 🤗https://huggingface.co/Daemontatox/PathFinderAI2.0 
Base Model(s)  unsloth/qwq-32b-preview-bnb-4bit   unsloth/qwq-32b-preview-bnb-4bit
Model Size32b
Required VRAM65.8 GB
Updated2025-02-05
MaintainerDaemontatox
Model Typeqwen2
Model Files  4.9 GB: 1-of-14   4.9 GB: 2-of-14   4.9 GB: 3-of-14   4.9 GB: 4-of-14   4.9 GB: 5-of-14   4.9 GB: 6-of-14   4.9 GB: 7-of-14   4.9 GB: 8-of-14   4.9 GB: 9-of-14   4.9 GB: 10-of-14   4.9 GB: 11-of-14   4.9 GB: 12-of-14   4.9 GB: 13-of-14   2.1 GB: 14-of-14
Supported Languagesen
Quantization Type4bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.47.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|vision_pad|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Context / RAM
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...pSeek R1 Distill Qwen 32B 4bit128K / 18.5 GB14410426
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Deepseek R1 Qwen32b Mlx 6bit128K / 25.5 GB22114
Qwen2.5 32B Bnb 4bit128K / 19.2 GB377493
...Distill Qwen 32B Japanese 4bit128K / 18.5 GB1612
...Distill Qwen 32B Japanese 8bit128K / 34.9 GB932
EVA Instruct 32B EXL2 4.0128K / 17.7 GB123
PathfinderAI32K / 65.8 GB520
...eview Gptqmodel 4bit Vortex V232K / 15.8 GB123216
...wen2.5 Coder 32B Instruct 3bit32K / 14.3 GB163
Note: green Score (e.g. "73.2") means that the model is better than Daemontatox/PathFinderAI2.0.

Rank the PathFinderAI2.0 Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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