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Internlm2 5 7B Chat by internlm

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Internlm2 5 7B Chat is an open-source language model by internlm. Features: 7b LLM, VRAM: 15.4GB, Context: 32K, License: other, LLM Explorer Score: 0.32.

  Arxiv:2403.17297   Autotrain compatible   Conversational   Custom code   Internlm2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/internlm/internlm2_5-7b-chat 

Internlm2 5 7B Chat Benchmarks

MMLU Pro: 30.85
GPQA: 12.98
MUSR: 16.29
BBH: 57.04
IFEval: 55.39 vs 88 (so35)-37.1%
MATH Lvl 5: 25.3
LLME Score: 0.32323
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Internlm2 5 7B Chat (internlm/internlm2_5-7b-chat)
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Internlm2 5 7B Chat Parameters and Internals

Model Type 
text-generation, chat
Use Cases 
Areas:
Research, Practical applications
Applications:
Chatbots, Educational tools, Data analysis
Primary Use Cases:
Mathematics reasoning, Knowledge inference, Discipline competence
Limitations:
Risk of biased or unexpected outputs
Considerations:
Monitor for biased or harmful content. Apply ethical usage guidelines.
Additional Notes 
The model supports enhanced tool use capabilities.
Supported Languages 
English (Proficient), Chinese (Proficient)
Training Details 
Data Sources:
Various datasets for reasoning, comprehension, and language proficiency
Methodology:
State-of-the-art techniques emphasizing reasoning and comprehension capabilities in practical scenarios
Context Length:
1000000
Model Architecture:
Supports tool use for gathering information from over 100 web pages
Safety Evaluation 
Methodologies:
Evaluation on 5 dimensions using OpenCompass
Findings:
High proficiency in language and reasoning tasks
Risk Categories:
Bias, Discrimination
Ethical Considerations:
Model may produce unexpected outputs including biases and harmful content
Responsible Ai Considerations 
Fairness:
Evaluated but potential for biases remains.
Transparency:
Open source with technical report provided.
Accountability:
Developers recommend monitoring for harm in applications.
Mitigation Strategies:
Efforts in training to ensure safety. Responsible use advised.
Input Output 
Input Format:
Text input for chat and data queries
Accepted Modalities:
text
Output Format:
Text responses
Performance Tips:
Use 'stream_chat' for efficient output rendering.
LLM NameInternlm2 5 7B Chat
Repository 🤗https://huggingface.co/internlm/internlm2_5-7b-chat 
Model Size7b
Required VRAM15.4 GB
Updated2025-10-27
Maintainerinternlm
Model Typeinternlm2
Model Files  1.9 GB: 1-of-8   1.9 GB: 2-of-8   2.0 GB: 3-of-8   1.9 GB: 4-of-8   2.0 GB: 5-of-8   1.9 GB: 6-of-8   2.0 GB: 7-of-8   1.8 GB: 8-of-8
Model ArchitectureInternLM2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.41.0
Is Biased0
Tokenizer ClassInternLM2Tokenizer
Padding Token</s>
Vocabulary Size92544
Torch Data Typebfloat16

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Rank the Internlm2 5 7B Chat 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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