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Mistral 7B Platypus Fp16 by bhenrym14

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  Autotrain compatible Dataset:garage-baind/open-plat...   Endpoints compatible   Fp16   Mistral   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/bhenrym14/mistral-7b-platypus-fp16 

Mistral 7B Platypus Fp16 Benchmarks

ARC: 61.6 vs 96.7 (so35)-36.3%
HellaSwag: 82.93 vs 95.3 (gpt4)-13%
MMLU: 63.16 vs 88.3 (so35)-28.5%
TruthfulQA: 46.96 vs 59 (gpt4)-20.4%
WinoGrande: 78.14 vs 87.5 (gpt4)-10.7%
GSM8K: 16.38 vs 96.4 (so35)-83%
LLME Score: 0.17844
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral 7B Platypus Fp16 (bhenrym14/mistral-7b-platypus-fp16)

Mistral 7B Platypus Fp16 Parameters and Internals

Model Type 
instruction tuned, fine-tuned
Training Details 
Data Sources:
garage-bAInd/Open-Platypus
Methodology:
QLoRA fine-tune
Training Time:
~9 hours
Hardware Used:
1x RTX 6000 Ada
Model Architecture:
Mistral
Input Output 
Performance Tips:
The `Mistral` architecture requires installation of `transformers` from source.
LLM NameMistral 7B Platypus Fp16
Repository 🤗https://huggingface.co/bhenrym14/mistral-7b-platypus-fp16 
Base Model(s)  Mistral 7B Platypus1k   lgaalves/mistral-7b-platypus1k
Model Size7b
Required VRAM14.4 GB
Updated2024-12-22
Maintainerbhenrym14
Model Typemistral
Model Files  9.9 GB: 1-of-2   4.5 GB: 2-of-2
Quantization Typefp16
Model ArchitectureMistralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.34.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than bhenrym14/mistral-7b-platypus-fp16.

Rank the Mistral 7B Platypus Fp16 Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Release v20241217
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