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Glaive Coder 7B by glaiveai

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  Autotrain compatible   Code   Codegen Dataset:glaiveai/glaive-code-a...   En   Endpoints compatible   Instruct   Llama   Pytorch   Region:us

Glaive Coder 7B Benchmarks

ARC: 42.66 vs 96.7 (so35)-55.9%
HellaSwag: 64.69 vs 95.3 (gpt4)-32.1%
MMLU: 37.15 vs 88.3 (so35)-57.9%
TruthfulQA: 39.88 vs 59 (gpt4)-32.4%
WinoGrande: 59.75 vs 87.5 (gpt4)-31.7%
GSM8K: 5.23 vs 96.4 (so35)-94.6%
LLME Score: 0.20122
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Glaive Coder 7B Parameters and Internals

Model Type 
code generation
Use Cases 
Areas:
code assistance
Applications:
single instruction following, multi-turn conversations
Primary Use Cases:
As a code assistant
Additional Notes 
Join the Code Models Arena for better understanding of user preference and suggest improvements via Discord.
Supported Languages 
en (Subtype: Engilsh)
Training Details 
Data Sources:
glaiveai/glaive-code-assistant
Data Volume:
~140k programming related problems and solutions
Methodology:
Fine-tuned on the CodeLlama-7b model. Uses a specific prompt format similar to CodeLlama-7b-Instruct.
Input Output 
Input Format:
~~[INST] <> {{ system_prompt }} <> {{ user_msg }} [/INST] {{ model_answer }}
Output Format:
Generates code outputs based on the provided instruction.
LLM NameGlaive Coder 7B
Repository 🤗https://huggingface.co/glaiveai/glaive-coder-7b 
Model Size7b
Required VRAM27 GB
Updated2024-11-21
Maintainerglaiveai
Model Typellama
Instruction-BasedYes
Model Files  27.0 GB
Supported Languagesen
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length16384
Model Max Length16384
Transformers Version4.32.0
Tokenizer ClassCodeLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32017
Torch Data Typefloat32
Glaive Coder 7B (glaiveai/glaive-coder-7b)

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

Rank the Glaive Coder 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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Release v20241110
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