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ECE PRYMMAL 0.5B FT V4 MUSR Mathis by matouLeLoup

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ECE PRYMMAL 0.5B FT V4 MUSR Mathis is an open-source language model by matouLeLoup. Features: 0.5b LLM, VRAM: 1GB, Context: 128K, LLM Explorer Score: 0.18.

  Dataset:allenai/qasc   En   Instruct   Model-index   Musr   Qwen2   Reasoning   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/matouLeLoup/ECE-PRYMMAL-0.5B-FT-V4-MUSR-Mathis 

ECE PRYMMAL 0.5B FT V4 MUSR Mathis Benchmarks

MMLU Pro: 8
GPQA: 1.79
MUSR: 4.13
BBH: 8.08
IFEval: 18.82 vs 88 (so35)-78.6%
MATH Lvl 5: 2.72
LLME Score: 0.18226
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
ECE PRYMMAL 0.5B FT V4 MUSR Mathis (matouLeLoup/ECE-PRYMMAL-0.5B-FT-V4-MUSR-Mathis)
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ECE PRYMMAL 0.5B FT V4 MUSR Mathis Parameters and Internals

LLM NameECE PRYMMAL 0.5B FT V4 MUSR Mathis
Repository 🤗https://huggingface.co/matouLeLoup/ECE-PRYMMAL-0.5B-FT-V4-MUSR-Mathis 
Model Size0.5b
Required VRAM1 GB
Updated2024-11-18
MaintainermatouLeLoup
Model Typeqwen2
Model Files  1.0 GB
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Context Length131072
Model Max Length131072
Transformers Version4.46.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

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ECE PRYMMAL 0.5B FT V4 MUSR128K / 2 GB60
Note: green Score (e.g. "73.2") means that the model is better than matouLeLoup/ECE-PRYMMAL-0.5B-FT-V4-MUSR-Mathis.

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Instruction Following and Task Automation  
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