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Samantha Mistral Instruct 7B Bulleted Notes GGUF by cognitivetech

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Samantha Mistral Instruct 7B Bulleted Notes GGUF is an open-source language model by cognitivetech. Features: 7b LLM, VRAM: 4.4GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.14.

Base model:quantized:quixiai/s... Base model:quixiai/samantha-mi...   Conversational   En   Endpoints compatible   Gguf   Instruct   Mistral   Notes   Quantized   Region:us   Samantha   Summary   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/cognitivetech/samantha-mistral-instruct-7b_bulleted-notes_GGUF 

Samantha Mistral Instruct 7b Bulleted Notes GGUF Benchmarks

LLME Score: 0.13635
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Samantha Mistral Instruct 7B Bulleted Notes GGUF (cognitivetech/samantha-mistral-instruct-7b_bulleted-notes_GGUF)
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Samantha Mistral Instruct 7B Bulleted Notes GGUF Parameters and Internals

Model Type 
text-generation, text-summarization
Use Cases 
Areas:
Research, Companionship, Long text summarization
Applications:
Book summarization, Comprehensive bulleted notes
Primary Use Cases:
Psychology text summarization
Limitations:
Does not engage in roleplay or romance
Additional Notes 
Dataset contains some improperly escaped characters, noted by the developer.
Supported Languages 
en (Excellent)
Training Details 
Data Sources:
Samantha-1.1 dataset, 5000 document-output example pairs
Data Volume:
20 epochs
Methodology:
Trained with fine-tuning on Samantha-1.1 dataset
Training Time:
2 hours
Hardware Used:
4x A100 80gb
Model Architecture:
based on mistral-7b-instruct
Safety Evaluation 
Methodologies:
Conversational restrictions in place
Risk Categories:
Sentience perception
Ethical Considerations:
Avoids topics of romance, roleplay, illegal activities
Responsible Ai Considerations 
Fairness:
No data provided
Transparency:
Open source, with extensive documentation and script access
Accountability:
Cognitive Computations is accountable
Mitigation Strategies:
No romance, roleplay, or illegal activity engagement, clearly expressed system prompts
Input Output 
Input Format:
ChatML format
Accepted Modalities:
text
Output Format:
Bulleted notes
Performance Tips:
Ensure input text is clearly structured for best summaries
Release Notes 
Version:
Initial Release
Date:
unknown
Notes:
First successful fine-tune for comprehensive bulleted notes
LLM NameSamantha Mistral Instruct 7b Bulleted Notes GGUF
Repository 🤗https://huggingface.co/cognitivetech/samantha-mistral-instruct-7b_bulleted-notes_GGUF 
Base Model(s)  Samantha Mistral Instruct 7B   cognitivecomputations/samantha-mistral-instruct-7b
Model Size7b
Required VRAM4.4 GB
Updated2025-10-28
Maintainercognitivetech
Model Typemistral
Instruction-BasedYes
Model Files  4.4 GB   5.1 GB   5.9 GB   7.7 GB   14.5 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel
Licenseapache-2.0

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Note: green Score (e.g. "73.2") means that the model is better than cognitivetech/samantha-mistral-instruct-7b_bulleted-notes_GGUF.

Rank the Samantha Mistral Instruct 7B Bulleted Notes GGUF 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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