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Internlm2 7B by internlm

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Internlm2 7B is an open-source language model by internlm. Features: 7b LLM, VRAM: 15.5GB, Context: 32K, License: other, LLM Explorer Score: 0.22, Arc: 58, HellaSwag: 81.2, MMLU: 65.2, GSM8K: 63.

  Arxiv:2403.17297   Custom code   Internlm2   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/internlm/internlm2-7b 

Internlm2 7B Benchmarks

ARC: 58.02 vs 96.7 (so35)-40%
HellaSwag: 81.24 vs 95.3 (gpt4)-14.8%
MMLU: 65.24 vs 88.3 (so35)-26.1%
GSM8K: 63 vs 96.4 (so35)-34.6%
LLME Score: 0.222
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Internlm2 7B (internlm/internlm2-7b)
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Internlm2 7B Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
academic research, commercial applications
Limitations:
Bias, discrimination, harmful content
Additional Notes 
InternLM2 is designed for ultra-large context handling and is aligned with conversational use cases via RLHF optimizations.
Input Output 
Input Format:
Text
Accepted Modalities:
text
Output Format:
Text
Performance Tips:
Using a GPU and loading the model in float16 is recommended for better performance and to prevent OOM errors.
Release Notes 
Version:
InternLM2-7B
Date:
2024
Notes:
Release of InternLM2 models with improved capabilities over the previous generation.
Version:
InternLM2-20B
Date:
2024
Notes:
Enhanced version with advanced reasoning and domain-specific corpus pretraining.
LLM NameInternlm2 7B
Repository 🤗https://huggingface.co/internlm/internlm2-7b 
Model Size7b
Required VRAM15.5 GB
Updated2026-05-27
Maintainerinternlm
Model Typeinternlm2
Model Files  10.0 GB: 1-of-2   5.5 GB: 2-of-2
Model ArchitectureInternLM2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.41.0
Is Biased0
Tokenizer ClassInternLM2Tokenizer
Padding Token</s>
Vocabulary Size92544
Torch Data Typebfloat16

Quantized Models of the Internlm2 7B

Model
Likes
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VRAM
...rnlm2 20B Llama 4.0bpw H6 EXL21111 GB

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Note: green Score (e.g. "73.2") means that the model is better than internlm/internlm2-7b.

Rank the Internlm2 7B 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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