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Neural Chat 7B V3 by Intel

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Neural Chat 7B V3 is an open-source language model by Intel. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, Fine-Tuned, HF Score: 58.5, LLM Explorer Score: 0.18, Arc: 67.2, HellaSwag: 83.3, MMLU: 62.3, TruthfulQA: 58.8, WinoGrande: 78.1, GSM8K: 1.2.

  Arxiv:2306.02707   Autotrain compatible Base model:finetune:mistralai/... Base model:mistralai/mistral-7...   Dataset:open-orca/slimorca   En   Endpoints compatible   Finetuned   Intel   Lora   Mistral   Model-index   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Intel/neural-chat-7b-v3 

Neural Chat 7B V3 Benchmarks

MMLU Pro: 18.87
GPQA: 5.59
MUSR: 23.02
BBH: 30.21
IFEval: 27.78 vs 88 (so35)-68.4%
ARC: 67.15 vs 96.7 (so35)-30.6%
HellaSwag: 83.29 vs 95.3 (gpt4)-12.6%
MMLU: 62.26 vs 88.3 (so35)-29.5%
TruthfulQA: 58.77 vs 59 (gpt4)-0.4%
WinoGrande: 78.06 vs 87.5 (gpt4)-10.8%
GSM8K: 1.21 vs 96.4 (so35)-98.7%
MATH Lvl 5: 2.95
LLME Score: 0.17769
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Neural Chat 7B V3 (Intel/neural-chat-7b-v3)
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Neural Chat 7B V3 Parameters and Internals

Model Type 
Large Language Model, text-generation
Use Cases 
Areas:
Research, Commercial applications
Primary Use Cases:
Language-related tasks
Limitations:
Fine-tuning required for specific tasks
Additional Notes 
Neural-chat-7b-v3 can produce factually incorrect output, and may generate lewd, biased, or otherwise offensive outputs. Safety testing is recommended before deployment.
Supported Languages 
en (high)
Training Details 
Data Sources:
Open-Orca/SlimOrca, Intel/orca_dpo_pairs
Methodology:
Direct Performance Optimization (DPO)
Context Length:
8192
Hardware Used:
Intel Gaudi 2 processor (8 cards)
Input Output 
Input Format:
Text
Accepted Modalities:
text
Output Format:
Text
Performance Tips:
Fine-tune the model for specific tasks to improve accuracy.
Release Notes 
Version:
v3
Date:
October, 2023
Notes:
Improvement in model performance on various benchmarks. Better alignment using the Direct Performance Optimization (DPO) method.
LLM NameNeural Chat 7B V3
Repository 🤗https://huggingface.co/Intel/neural-chat-7b-v3 
Base Model(s)  mistralai/Mistral-7B-v0.1   mistralai/Mistral-7B-v0.1
Model Size7b
Required VRAM14.4 GB
Updated2025-09-23
MaintainerIntel
Model Typemistral
Model Files  9.9 GB: 1-of-2   4.5 GB: 2-of-2   9.9 GB: 1-of-2   4.5 GB: 2-of-2
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.34.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
LoRA ModelYes
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than Intel/neural-chat-7b-v3.

Rank the Neural Chat 7B V3 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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