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Eros 7B Test by tavtav

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Eros 7B Test is an open-source language model by tavtav. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.13.

  Conversational   En   Endpoints compatible   Instruct   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/tavtav/eros-7b-test 

Eros 7B Test Benchmarks

LLME Score: 0.12834
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Eros 7B Test (tavtav/eros-7b-test)
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Eros 7B Test Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
fictional writing, entertainment
Primary Use Cases:
ChatRP, story generation
Limitations:
not fine-tuned to be safe and harmless, may produce socially unacceptable or undesirable text, outputs might often be factually wrong or misleading
Additional Notes 
This is considered an unofficial, experimental model. Notable issues include occasional misspellings, random formatting artifacts, and repeated phrases.
Training Details 
Data Sources:
PIPPA dataset
Data Volume:
22K token examples
Methodology:
Finetuning on Mistral-7B, trained on ChatML format
Input Output 
Input Format:
ChatML Instruct Settings
Performance Tips:
Temperature, and Min P values can be adjusted to greater or lower values depending on generation preferences.
LLM NameEros 7B Test
Repository 🤗https://huggingface.co/tavtav/eros-7b-test 
Model Size7b
Required VRAM14.4 GB
Updated2026-01-04
Maintainertavtav
Model Typemistral
Instruction-BasedYes
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3   0.3 GB
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32032
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than tavtav/eros-7b-test.

Rank the Eros 7B Test 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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