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NeuroCom V2 4B by FourOhFour

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  Autotrain compatible   Conversational   En   Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/FourOhFour/NeuroCom_v2_4B 

NeuroCom V2 4B Benchmarks

LLME Score: 0.22551
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
NeuroCom V2 4B (FourOhFour/NeuroCom_v2_4B)

NeuroCom V2 4B Parameters and Internals

Model Type 
General Assistant, RP Model
Use Cases 
Primary Use Cases:
General assistant, Role play
Additional Notes 
Fixes several issues with the original NeuroCom train and is aimed at better generalization capabilities.
Supported Languages 
English (High)
Training Details 
Data Volume:
100 million high quality tokens
Methodology:
Noisy training approach by Kalomaze; Healed and instruct/RP tuned
Context Length:
8000
LLM NameNeuroCom V2 4B
Repository 🤗https://huggingface.co/FourOhFour/NeuroCom_v2_4B 
Model Size4b
Required VRAM9 GB
Updated2024-12-21
MaintainerFourOhFour
Model Typellama
Model Files  5.0 GB: 1-of-2   4.0 GB: 2-of-2   0.0 GB
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.45.0.dev0
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|finetune_right_pad_id|>
Vocabulary Size128256
Torch Data Typebfloat16

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Completion4B128K / 9 GB240
Note: green Score (e.g. "73.2") means that the model is better than FourOhFour/NeuroCom_v2_4B.

Rank the NeuroCom V2 4B Capabilities

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Instruction Following and Task Automation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217
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