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Gen Sim by Gen-Sim

 »  All LLMs  »  Gen-Sim  »  Gen Sim   URL Share it on

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  Autotrain compatible   Codegen   Endpoints compatible   Instruct   Llama   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/Gen-Sim/Gen-Sim 

Gen Sim Benchmarks

LLME Score: 0.10655
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gen Sim (Gen-Sim/Gen-Sim)
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Gen Sim Parameters and Internals

Model Type 
code generation
Use Cases 
Areas:
robotic simulation tasks, code generation
Applications:
research, education, industry projects
Primary Use Cases:
simulation task code generation
Limitations:
may not handle tasks outside of training scope, limited to simulation-focused tasks
Considerations:
Ensure outputs are reviewed for correctness
Additional Notes 
Optimized for code generation in robotic simulations
Training Details 
Data Sources:
100 simulation tasks generated by GPT-4 and humans
Methodology:
Finetuning
Input Output 
Input Format:
[INST] <RLTask> <Description> [Code Snippet]
Accepted Modalities:
text
Output Format:
Python code block
LLM NameGen Sim
Repository 🤗https://huggingface.co/Gen-Sim/Gen-Sim 
Model Size13b
Required VRAM0.3 GB
Updated2025-09-10
MaintainerGen-Sim
Model Typellama
Instruction-BasedYes
Model Files  0.3 GB: 1-of-3   0.0 GB: 2-of-3   0.0 GB: 3-of-3
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licensemit
Context Length16384
Model Max Length16384
Transformers Version4.29.2
Vocabulary Size32016
Torch Data Typefloat16

Best Alternatives to Gen Sim

Best Alternatives
Context / RAM
Downloads
Likes
NexusRaven V2 13B16K / 26 GB1378469
CodeLlama 13B Instruct Hf16K / 26 GB20525154
CodeLlama 13B MORepair16K / 26 GB52
CodeLlama 13B Instruct Hf16K / 26 GB118425
TableLLM 13B16K / 26 GB130329
NexusRaven 13B16K / 26 GB13104
Panda Coder 13B16K / 26 GB1413
... Llama 2 13B Instruct Text2sql16K / 26 GB2927
CodeLlama 13B Instruct Fp1616K / 26 GB264728
...Llama 13B Instruct Hf 4bit MLX16K / 7.8 GB13622
Note: green Score (e.g. "73.2") means that the model is better than Gen-Sim/Gen-Sim.

Rank the Gen Sim 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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