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CatPPT Base by rishiraj

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  Autotrain compatible   Endpoints compatible   Merge   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/rishiraj/CatPPT-base 

CatPPT Base Benchmarks

ARC: 67.92 vs 96.7 (so35)-29.8%
HellaSwag: 86.64 vs 95.3 (gpt4)-9.1%
MMLU: 65.26 vs 88.3 (so35)-26.1%
TruthfulQA: 61.72 vs 59 (gpt4)4.6%
WinoGrande: 81.29 vs 87.5 (gpt4)-7.1%
GSM8K: 70.66 vs 96.4 (so35)-26.7%
LLME Score: 0.20984
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
CatPPT Base (rishiraj/CatPPT-base)

CatPPT Base Parameters and Internals

Model Type 
text generation, chatbot
Training Details 
Data Sources:
no_robots dataset
Methodology:
Merged openchat and neuralchat models using Gradient SLERP method
Training Time:
15th and 17th December, 2023
LLM NameCatPPT Base
Repository 🤗https://huggingface.co/rishiraj/CatPPT-base 
Model Size7b
Required VRAM14.4 GB
Updated2024-12-22
Maintainerrishiraj
Model Typemistral
Model Files  9.9 GB: 1-of-2   4.5 GB: 2-of-2
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.35.2
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 rishiraj/CatPPT-base.

Rank the CatPPT Base Capabilities

🆘 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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Release v20241217
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