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Saba1 7B by Sakalti

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Saba1 7B is an open-source language model by Sakalti. Features: 7b LLM, VRAM: 14.8GB, Context: 128K, Merged, LLM Explorer Score: 0.25.

  Merged Model   Arxiv:2306.01708   Base model:aidc-ai/marco-o1   Base model:sakalti/model-3   Conversational   Endpoints compatible   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Sakalti/Saba1-7B 

Saba1 7B Benchmarks

LLME Score: 0.25136
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Saba1 7B (Sakalti/Saba1-7B)
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Saba1 7B Parameters and Internals

LLM NameSaba1 7B
Repository 🤗https://huggingface.co/Sakalti/Saba1-7B 
Base Model(s)  Marco O1   Model 3   AIDC-AI/Marco-o1   Sakalti/model-3
Merged ModelYes
Model Size7b
Required VRAM14.8 GB
Updated2026-05-26
MaintainerSakalti
Model Typeqwen2
Model Files  1.1 GB: 1-of-16   1.1 GB: 2-of-16   0.9 GB: 3-of-16   0.9 GB: 4-of-16   0.9 GB: 5-of-16   0.9 GB: 6-of-16   0.9 GB: 7-of-16   0.9 GB: 8-of-16   0.9 GB: 9-of-16   0.9 GB: 10-of-16   0.9 GB: 11-of-16   0.9 GB: 12-of-16   0.9 GB: 13-of-16   0.9 GB: 14-of-16   0.9 GB: 15-of-16   0.9 GB: 16-of-16
Model ArchitectureQwen2ForCausalLM
Context Length131072
Model Max Length131072
Transformers Version4.45.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to Saba1 7B

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2.5 7B Preview986K / 15.2 GB100
Qwen2.5 7B Instruct 1M986K / 15.4 GB32350369
Hush Qwen2.5 7B V1.1986K / 15.2 GB191
Hush Qwen2.5 7B V1.2986K / 15.2 GB31
Hush Qwen2.5 7B Preview986K / 15.2 GB400
Hush Qwen2.5 7B V1.4986K / 15.2 GB41
Hush Qwen2.5 7B V1.3986K / 15.2 GB182
Hush Qwen2.5 7B RP V1.4 1M986K / 15.2 GB172
Qwen 2.5 7B Exp Sce986K / 15.2 GB72
Qwen2.5 7B MixStock V0.1986K / 15.2 GB113
Note: green Score (e.g. "73.2") means that the model is better than Sakalti/Saba1-7B.

Rank the Saba1 7B 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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