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Merlinite 7B by alinaryan

 »  All LLMs  »  alinaryan  »  Merlinite 7B   URL Share it on

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  Autotrain compatible   Endpoints compatible   Gguf   Mistral   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/alinaryan/merlinite-7b 

Merlinite 7B Benchmarks

LLME Score: 0.17626
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Merlinite 7B (alinaryan/merlinite-7b)

Merlinite 7B Parameters and Internals

Model Type 
Synthetic Data Generation
Use Cases 
Areas:
Data Generation
Applications:
Research, Testing, Automation
Primary Use Cases:
Synthetic data generation for various purposes
Limitations:
Requires setup of environment and dependencies, Access tokens needed for certain operations
Considerations:
Ensure proper setup of environment variables and configurations.
Additional Notes 
This pipeline helps in generating synthetic data efficiently through automation and can be customized for different branches in taxonomy.
Input Output 
Output Format:
YAML and data files generated in specified directories.
Performance Tips:
Ensure correct environment variable setup for accurate data generation.
LLM NameMerlinite 7B
Repository 🤗https://huggingface.co/alinaryan/merlinite-7b 
Base Model(s)  Merlinite 7B Pt   instructlab/merlinite-7b-pt
Model Size7b
Required VRAM14.4 GB
Updated2025-02-22
Maintaineralinaryan
Model Typemistral
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3   4.4 GB
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureMistralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.38.1
Tokenizer ClassLlamaTokenizer
Padding Token<|pad|>
Vocabulary Size32008
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than alinaryan/merlinite-7b.

Rank the Merlinite 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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Release v20241227
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