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Small Fut Final by Dongwookss

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  Autotrain compatible   Conversational Dataset:dongwookss/q a korean ...   Endpoints compatible   Ko   Lora   Mistral   Region:us   Safetensors   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF πŸ€—: https://huggingface.co/Dongwookss/small_fut_final 

Small Fut Final Benchmarks

LLME Score: 0.20644
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Small Fut Final (Dongwookss/small_fut_final)

Small Fut Final Parameters and Internals

Model Type 
chatbot
Use Cases 
Areas:
Research, Commercial applications
Applications:
Chatbots for futsal domain
Primary Use Cases:
Futsal assistant helper chatbot
Considerations:
Model answers are based on provided context; outside the context, it responds with uncertainty.
Additional Notes 
The model uses speech in the 'ν•΄μš”' style for responses, ending with a friendly 'ν’‹ν’‹~!'
Supported Languages 
ko (high)
Training Details 
Data Sources:
q_a_korean_futsal
Methodology:
LLM νŒŒμΈνŠœλ‹ (fine-tuning) with LoRA and SFT Trainer
Context Length:
4096
Hardware Used:
Colab environment with L4 GPU
Input Output 
Input Format:
Chat input with instruction and response mechanism
Accepted Modalities:
Text
Output Format:
Text response
LLM NameSmall Fut Final
Repository πŸ€—https://huggingface.co/Dongwookss/small_fut_final 
Model Size7.2b
Required VRAM14.4 GB
Updated2024-12-22
MaintainerDongwookss
Model Files  0.2 GB   4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Supported Languagesko
Model ArchitectureAutoModelForCausalLM
Licenseapache-2.0
Model Max Length32768
Is Biasednone
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Moduleso_proj|v_proj|down_proj|gate_proj|q_proj|k_proj|up_proj
LoRA Alpha32
LoRA Dropout0.05
R Param16

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Note: green Score (e.g. "73.2") means that the model is better than Dongwookss/small_fut_final.

Rank the Small Fut Final Capabilities

πŸ†˜ 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217
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