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Psych Qwen 32B by Compumacy

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Psych Qwen 32B is an open-source language model by Compumacy. Features: 32b LLM, VRAM: 65.8GB, Context: 40K, License: apache-2.0, LLM Explorer Score: 0.19.

  Arxiv:2106.09685   Arxiv:2309.16609 Base model:adapter:unsloth/qwe...   Base model:unsloth/qwen3-32b   Clinical-assessment   Conversational Dataset:daemontatox/psy-data-b...   En   Endpoints compatible   Lora   Medical   Mental-health   Psychiatry   Psychology   Qwen   Qwen3   Region:us   Safetensors   Sharded   Tensorflow   Unsloth
Model Card on HF 🤗: https://huggingface.co/Compumacy/Psych_Qwen_32B 

Psych Qwen 32B Benchmarks

LLME Score: 0.19377
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Psych Qwen 32B (Compumacy/Psych_Qwen_32B)
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Psych Qwen 32B Parameters and Internals

LLM NamePsych Qwen 32B
Repository 🤗https://huggingface.co/Compumacy/Psych_Qwen_32B 
Base Model(s)  Qwen3 32B   unsloth/Qwen3-32B
Model Size32b
Required VRAM65.8 GB
Updated2026-06-25
MaintainerCompumacy
Model Typeqwen3
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
Model ArchitectureQwen3ForCausalLM
Licenseapache-2.0
Context Length40960
Model Max Length40960
Transformers Version4.52.4
Tokenizer ClassQwen2Tokenizer
Padding Token<|vision_pad|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

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...ll Qwen3 32B Preview7 QAT 200K195K / 65.8 GB33
...ll Qwen3 32B Preview6 QAT 200K195K / 65.8 GB52
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Qwen3 32B40K / 65.8 GB644615
Qwen3 32B NVFP440K / 20.7 GB24624117
Assistant Pepe 32B40K / 65.5 GB34452
OpenThinkerAgent 32B40K / 65.8 GB2608
FrogBoss 32B 251040K / 65.8 GB1210629
Nemotron Terminal 32B40K / 65.6 GB186938
Note: green Score (e.g. "73.2") means that the model is better than Compumacy/Psych_Qwen_32B.

Rank the Psych Qwen 32B 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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