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SAM GPTQ by TheBloke

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SAM GPTQ is an open-source language model by TheBloke. Features: 1.2b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.11.

  4-bit   Autotrain compatible Base model:quantized:superagi/...   Base model:superagi/sam   En   Gptq   Mistral   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/SAM-GPTQ 

SAM GPTQ Benchmarks

LLME Score: 0.11081
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
SAM GPTQ (TheBloke/SAM-GPTQ)
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SAM GPTQ Parameters and Internals

Model Type 
mistral
Use Cases 
Areas:
reasoning
Applications:
multi-hop reasoning
Primary Use Cases:
task breakdown, improved reasoning
Limitations:
Not suitable for conversations, simple Q&A
Considerations:
Better reasoning using high-quality data, not suitable for production due to lack of moderation mechanisms.
Additional Notes 
SAM is a demonstration of advanced reasoning using less but high-quality data, not suitable for production due to lack of guardrails.
Supported Languages 
en (High)
Training Details 
Data Sources:
OpenSource LLMs
Data Volume:
97% smaller dataset compared to other baseline models
Methodology:
Fine-tuned using a smaller, high-quality dataset
Training Time:
4 hours
Hardware Used:
NVIDIA 6 x H100 SxM (80GB)
Model Architecture:
Mistral 7B
Input Output 
Input Format:
[INST] {prompt} [/INST]
Accepted Modalities:
text
Output Format:
textual response
Performance Tips:
Suggested temperature for optimal performance is 0.3
LLM NameSAM GPTQ
Repository 🤗https://huggingface.co/TheBloke/SAM-GPTQ 
Model NameSAM
Model CreatorSuperAGI
Base Model(s)  SAM   SuperAGI/SAM
Model Size1.2b
Required VRAM4.2 GB
Updated2025-09-28
MaintainerTheBloke
Model Typemistral
Model Files  4.2 GB
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/SAM-GPTQ.

Rank the SAM GPTQ 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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