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Autogressive 32B by Multiverse4FM

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Autogressive 32B is an open-source language model by Multiverse4FM. Features: 32b LLM, VRAM: 131.5GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.19.

  Arxiv:2506.09991 Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-32b-in...   Conversational Dataset:multiverse4fm/autoregr... Dataset:multiverse4fm/multiver...   Dataset:simplescaling/s1k-1.1   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Multiverse4FM/Autogressive-32B 

Autogressive 32B Benchmarks

LLME Score: 0.18861
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Autogressive 32B (Multiverse4FM/Autogressive-32B)
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Autogressive 32B Parameters and Internals

LLM NameAutogressive 32B
Repository 🤗https://huggingface.co/Multiverse4FM/Autogressive-32B 
Base Model(s)  Qwen/Qwen2.5-32B-Instruct   Qwen/Qwen2.5-32B-Instruct
Model Size32b
Required VRAM131.5 GB
Updated2026-05-19
MaintainerMultiverse4FM
Model Typeqwen2
Instruction-BasedYes
Model Files  4.5 GB: 1-of-29   4.7 GB: 2-of-29   4.5 GB: 3-of-29   4.5 GB: 4-of-29   4.7 GB: 5-of-29   4.5 GB: 6-of-29   4.5 GB: 7-of-29   4.7 GB: 8-of-29   4.5 GB: 9-of-29   4.5 GB: 10-of-29   4.7 GB: 11-of-29   4.5 GB: 12-of-29   4.5 GB: 13-of-29   4.7 GB: 14-of-29   4.5 GB: 15-of-29   4.5 GB: 16-of-29   4.7 GB: 17-of-29   4.5 GB: 18-of-29   4.5 GB: 19-of-29   4.7 GB: 20-of-29   4.5 GB: 21-of-29   4.5 GB: 22-of-29   4.7 GB: 23-of-29   4.5 GB: 24-of-29   4.5 GB: 25-of-29   4.7 GB: 26-of-29   4.5 GB: 27-of-29   4.5 GB: 28-of-29   3.7 GB: 29-of-29   0.0 GB
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.46.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|fim_pad|>
Vocabulary Size152064
Torch Data Typefloat32
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than Multiverse4FM/Autogressive-32B.

Rank the Autogressive 32B Capabilities

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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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