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MKLLM 7B Instruct by trajkovnikola

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  Autotrain compatible   Axolotl   Conversational   En   Endpoints compatible   Instruct   Mistral   Mk   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/trajkovnikola/MKLLM-7B-Instruct 

MKLLM 7B Instruct Benchmarks

LLME Score: 0.19737
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MKLLM 7B Instruct (trajkovnikola/MKLLM-7B-Instruct)

MKLLM 7B Instruct Parameters and Internals

Model Type 
open-source, instruction-tuned
Use Cases 
Areas:
Macedonian language processing
Applications:
Conversational AI, Macedonian NLP tasks
Limitations:
May hallucinate or be inaccurate on Macedonian topics
Additional Notes 
MKLLM-7B-Instruct writes more coherent Macedonian compared to other models.
Supported Languages 
Macedonian (high proficiency), English (moderate proficiency)
Training Details 
Data Sources:
Macedonian text, English text
Data Volume:
~300M tokens, repeated over 2 epochs
Methodology:
Instruction training with axolotl using chatml format
Safety Evaluation 
Ethical Considerations:
May produce factually incorrect outputs, especially on Macedonian topics due to limited data.
Input Output 
Input Format:
chatml
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Use chatml format for prompts.
LLM NameMKLLM 7B Instruct
Repository 🤗https://huggingface.co/trajkovnikola/MKLLM-7B-Instruct 
Model Size7b
Required VRAM14.4 GB
Updated2025-02-22
Maintainertrajkovnikola
Model Typemistral
Instruction-BasedYes
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Supported Languagesmk en
Model ArchitectureMistralForCausalLM
Licensecc-by-nc-sa-4.0
Context Length32768
Model Max Length32768
Transformers Version4.41.1
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32002
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than trajkovnikola/MKLLM-7B-Instruct.

Rank the MKLLM 7B Instruct 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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Release v20241227
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