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Dolphin 2.2.1 Mistral 7B GPTQ by TheBloke

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  4-bit   Autotrain compatible Base model:cognitivecomputatio... Base model:quantized:cognitive...   Dataset:ehartford/dolphin Dataset:jondurbin/airoboros-2....   En   Gptq   Mistral   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/dolphin-2.2.1-mistral-7B-GPTQ 

Dolphin 2.2.1 Mistral 7B GPTQ Benchmarks

LLME Score: 0.12319
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Dolphin 2.2.1 Mistral 7B GPTQ (TheBloke/dolphin-2.2.1-mistral-7B-GPTQ)
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Dolphin 2.2.1 Mistral 7B GPTQ Parameters and Internals

Model Type 
mistral
Use Cases 
Areas:
open-source, AI research
Applications:
conversational AI, personal advice, text generation
Primary Use Cases:
Creative writing, Personal assistant tasks
Limitations:
Highly compliant; suitable for controlled environments., Not recommended to be used without custom alignment layers.
Considerations:
Model is highly compliant, monitor for ethical use.
Additional Notes 
Ensure alignment layers are implemented when deploying models to handle responsive behavior responsibly.
Supported Languages 
en (English)
Training Details 
Data Sources:
ehartford/dolphin, jondurbin/airoboros-2.2.1
Methodology:
Training for 4 epochs on uncensored, deduped, and quality filtered data. Included datasets increase creativity and empathy.
Training Time:
48 hours on 4x A100s
Hardware Used:
4x A100 GPUs
Model Architecture:
Based on mistralAI
Responsible Ai Considerations 
Accountability:
Content responsibility lies with the user.
Mitigation Strategies:
Users are advised to implement own alignment layers.
Input Output 
Input Format:
ChatML format
Accepted Modalities:
text
Output Format:
Text generation in response to prompts
Performance Tips:
Ensure suitable hardware for fast inference; utilize provided quantization options to optimize performance.
Release Notes 
Notes:
Checkpoint release to fix overfitting; includes empathy and improved conversation features.
Notes:
Training sponsored by a16z, improvement in compliance and uncensored nature. Removed alignment and bias filtering from datasets.
LLM NameDolphin 2.2.1 Mistral 7B GPTQ
Repository 🤗https://huggingface.co/TheBloke/dolphin-2.2.1-mistral-7B-GPTQ 
Model NameDolphin 2.2.1 Mistral 7B
Model CreatorEric Hartford
Base Model(s)  ehartford/dolphin-2.2.1-mistral-7b   ehartford/dolphin-2.2.1-mistral-7b
Model Size7b
Required VRAM4.2 GB
Updated2025-09-23
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 Version4.34.1
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32002
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/dolphin-2.2.1-mistral-7B-GPTQ.

Rank the Dolphin 2.2.1 Mistral 7B 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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