Gen Sim by Gen-Sim

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  Autotrain compatible   Codegen   Endpoints compatible   Instruct   Llama   Pytorch   Region:us   Sharded
Model Card on HF ๐Ÿค—: https://huggingface.co/Gen-Sim/Gen-Sim 

Gen Sim Benchmarks

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)

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 ๐Ÿค—https://huggingface.co/Gen-Sim/Gen-Sim 
Model Size13b
Required VRAM0.3 GB
Updated2024-12-22
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
CodeLlama 13B MORepair16K / 26 GB26502
NexusRaven V2 13B16K / 26 GB3919465
CodeLlama 13B Instruct Hf16K / 26 GB16223144
CodeLlama 13B Instruct Hf16K / 26 GB99318
TableLLM 13B16K / 26 GB23525
... Llama 2 13B Instruct Text2sql16K / 26 GB732727
NexusRaven 13B16K / 26 GB158103
Panda Coder 13B16K / 26 GB8613
CodeLlama 13B Instruct Fp1616K / 26 GB200629
...Llama 13B Instruct Hf 4bit MLX16K / 7.8 GB752
Note: green Score (e.g. "73.2") means that the model is better than Gen-Sim/Gen-Sim.

Rank the Gen Sim Capabilities

๐Ÿ†˜ 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! ๐ŸŒŸ

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 v20241217