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Neural Chat Mini V2.2 1.8B by M4-ai

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Neural Chat Mini V2.2 1.8B is an open-source language model by M4-ai. Features: 1.8b LLM, VRAM: 3.7GB, Context: 32K, License: other, Instruction-Based, LLM Explorer Score: 0.17, Arc: 35.2, HellaSwag: 60.1, MMLU: 43, GSM8K: 18.7.

  Conversational   Dataset:camel-ai/biology   Dataset:camel-ai/chemistry   Dataset:camel-ai/math   Dataset:camel-ai/physics Dataset:jondurbin/airoboros-3....   Dataset:ldjnr/capybara   Dataset:m-a-p/code-feedback Dataset:maziyarpanahi/wizardlm... Dataset:microsoft/orca-math-wo...   Dataset:open-orca/slimorca   En   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/M4-ai/neural-chat-mini-v2.2-1.8B 

Neural Chat Mini V2.2 1.8B Benchmarks

ARC: 35.15 vs 96.7 (so35)-63.7%
HellaSwag: 60.06 vs 95.3 (gpt4)-37%
MMLU: 42.99 vs 88.3 (so35)-51.3%
GSM8K: 18.65 vs 96.4 (so35)-80.7%
LLME Score: 0.16694
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Neural Chat Mini V2.2 1.8B (M4-ai/neural-chat-mini-v2.2-1.8B)
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Neural Chat Mini V2.2 1.8B Parameters and Internals

Model Type 
general-purpose assistant, question answering, chain-of-thought
Use Cases 
Applications:
math, coding, writing
Primary Use Cases:
general-purpose assistant, question answering, chain-of-thought
Considerations:
Users should be made aware of the risks, biases and limitations of the model.
Supported Languages 
English (proficient), Chinese (potentially proficient)
Training Details 
Data Sources:
Open-Orca/SlimOrca, m-a-p/Code-Feedback, MaziyarPanahi/WizardLM_evol_instruct_V2_196k, camel-ai/math, camel-ai/physics, camel-ai/biology, camel-ai/chemistry, LDJnr/Capybara, jondurbin/airoboros-3.2, microsoft/orca-math-word-problems-200k, mlabonne/orpo-dpo-mix-40k
Methodology:
fine-tuned using SFT and DPOP
Context Length:
2048
Hardware Used:
8 Kaggle TPUs
Responsible Ai Considerations 
Fairness:
Users should be made aware of the risks, biases and limitations of the model.
Input Output 
Performance Tips:
Users should be made aware of the risks, biases and limitations of the model.
LLM NameNeural Chat Mini V2.2 1.8B
Repository 🤗https://huggingface.co/M4-ai/neural-chat-mini-v2.2-1.8B 
Model Size1.8b
Required VRAM3.7 GB
Updated2026-05-10
MaintainerM4-ai
Model Typeqwen2
Instruction-BasedYes
Model Files  2.0 GB: 1-of-2   1.7 GB: 2-of-2
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

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Rank the Neural Chat Mini V2.2 1.8B 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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