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MFANN3bv0.7.10 by netcat420

 »  All LLMs  »  netcat420  »  MFANN3bv0.7.10   URL Share it on

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  Merged Model   Arxiv:2306.01708   Autotrain compatible Base model:liminerity/phigment... Base model:netcat420/mfann3bv0... Base model:netcat420/mfann3bv0... Base model:netcat420/mfann3bv0...   Endpoints compatible   Phi   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/netcat420/MFANN3bv0.7.10 

MFANN3bv0.7.10 Benchmarks

ARC: 62.12 vs 96.7 (so35)-35.8%
HellaSwag: 77.08 vs 95.3 (gpt4)-19.1%
MMLU: 56.33 vs 88.3 (so35)-36.2%
TruthfulQA: 53.27 vs 59 (gpt4)-9.7%
WinoGrande: 76.64 vs 87.5 (gpt4)-12.4%
GSM8K: 57.54 vs 96.4 (so35)-40.3%
LLME Score: 0.20589
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MFANN3bv0.7.10 (netcat420/MFANN3bv0.7.10)

MFANN3bv0.7.10 Parameters and Internals

Additional Notes 
This model is a merge of pre-trained language models.
Training Details 
Methodology:
Merged using TIES method
LLM NameMFANN3bv0.7.10
Repository 🤗https://huggingface.co/netcat420/MFANN3bv0.7.10 
Base Model(s)  netcat420/MFANN3bv0.3   netcat420/MFANN3bv0.7   Phigments12   netcat420/MFANN3bv0.6   netcat420/MFANN3bv0.3   netcat420/MFANN3bv0.7   liminerity/Phigments12   netcat420/MFANN3bv0.6
Merged ModelYes
Model Size2.8b
Required VRAM5.6 GB
Updated2025-02-22
Maintainernetcat420
Model Typephi
Model Files  5.6 GB: 1-of-1
Model ArchitecturePhiForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.40.2
Tokenizer ClassCodeGenTokenizer
Vocabulary Size51200
Torch Data Typefloat16

Best Alternatives to MFANN3bv0.7.10

Best Alternatives
Context / RAM
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MFANN3bv0.24128K / 11.1 GB160
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MFANN3bv1.3128K / 11.1 GB250
MFANN3bv0.23128K / 11.1 GB360
MFANN3bv1.1128K / 11.1 GB130
MFANN3b SFT128K / 5.6 GB650
MFANN3b Rebase128K / 11.1 GB130
MFANN3bv1.2126K / 11.1 GB390
Note: green Score (e.g. "73.2") means that the model is better than netcat420/MFANN3bv0.7.10.

Rank the MFANN3bv0.7.10 Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
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Release v20241227
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