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Pip Code Bandit by PipableAI

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  Autotrain compatible   Basemodel   Causallm   Code   Code2doc   Codellama modified archi   Conversational   Cpp   Docstring   Document   Documentation   En   Endpoints compatible   Function calling   Instruct   Instruction tuned   Java   Llama   Plan   Planner   Python   Pytorch   Region:us   Safetensors   Sql   Unit tests
Model Card on HF 🤗: https://huggingface.co/PipableAI/pip-code-bandit 

Pip Code Bandit Benchmarks

LLME Score: 0.15191
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Pip Code Bandit (PipableAI/pip-code-bandit)
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Pip Code Bandit Parameters and Internals

Model Type 
text generation, function calling, instruction tuning
Use Cases 
Areas:
research, commercial applications
Primary Use Cases:
complex planning of sequential function calls, function calling, code generation, doc generation, sql generation
Supported Languages 
python (full proficiency), java (full proficiency), cpp (full proficiency), sql (full proficiency)
Training Details 
Data Sources:
simulated environments, code datasets, function documentation, open source datasets
Methodology:
RL tuned
Context Length:
16384
LLM NamePip Code Bandit
Repository 🤗https://huggingface.co/PipableAI/pip-code-bandit 
Model Size1.3b
Required VRAM2.7 GB
Updated2025-09-23
MaintainerPipableAI
Model Typellama
Instruction-BasedYes
Model Files  2.7 GB
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length16384
Model Max Length16384
Transformers Version4.40.2
Tokenizer ClassLlamaTokenizer
Padding Token<｜end▁of▁sentence｜>
Vocabulary Size32256
Torch Data Typebfloat16

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Pip Api Expert16K / 5.4 GB383
... 1.3B Instruct Trt Int4 G64 Hf16K / 0.9 GB80
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...t Structured Output Peft Merge16K / 2.7 GB60
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Note: green Score (e.g. "73.2") means that the model is better than PipableAI/pip-code-bandit.

Rank the Pip Code Bandit 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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