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Llama 7B Rollercoaster V2 by ncsgobubble

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Llama 7B Rollercoaster V2 is an open-source language model by ncsgobubble. Features: 7b LLM, VRAM: 13.5GB, Context: 4K, License: apache-2.0, Merged, HF Score: 51.2, LLM Explorer Score: 0.14, Arc: 52.8, HellaSwag: 78.2, MMLU: 49.8, TruthfulQA: 43.6, WinoGrande: 73.2, GSM8K: 9.6.

  Merged Model Base model:finetune:suvajitgb/... Base model:suvajitgb/rollercoa...   Conversational   Endpoints compatible   Llama   Meta-llama/llama-2-7b-chat-hf   Model-index   Region:us   Safetensors   Sharded Suvajitgb/rollercoaster emotio...   Tensorflow
Model Card on HF 🤗: https://huggingface.co/ncsgobubble/Llama-7B-rollercoaster_v2 

Llama 7B Rollercoaster V2 Benchmarks

ARC: 52.82 vs 96.7 (so35)-45.4%
HellaSwag: 78.22 vs 95.3 (gpt4)-17.9%
MMLU: 49.8 vs 88.3 (so35)-43.6%
TruthfulQA: 43.62 vs 59 (gpt4)-26.1%
WinoGrande: 73.16 vs 87.5 (gpt4)-16.4%
GSM8K: 9.55 vs 96.4 (so35)-90.1%
LLME Score: 0.14148
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 7B Rollercoaster V2 (ncsgobubble/Llama-7B-rollercoaster_v2)
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Llama 7B Rollercoaster V2 Parameters and Internals

Model Type 
text-generation
Additional Notes 
Llama-7B-rollercoaster_v2 is a merge of meta-llama/Llama-2-7b-chat-hf and SuvajitGB/rollercoaster_emotions_v2 using LazyMergekit.
LLM NameLlama 7B Rollercoaster V2
Repository 🤗https://huggingface.co/ncsgobubble/Llama-7B-rollercoaster_v2 
Base Model(s)  Rollercoaster Emotions V2   SuvajitGB/rollercoaster_emotions_v2
Merged ModelYes
Model Size7b
Required VRAM13.5 GB
Updated2026-02-26
Maintainerncsgobubble
Model Typellama
Model Files  9.9 GB: 1-of-2   3.6 GB: 2-of-2
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than ncsgobubble/Llama-7B-rollercoaster_v2.

Rank the Llama 7B Rollercoaster V2 Capabilities

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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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