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Llama3 8B Instruct Code by ibivibiv

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  4-bit   Adapter   Axolotl Base model:adapter:meta-llama/... Base model:meta-llama/meta-lla...   Bitsandbytes   En   Finetuned   Generated from trainer   Instruct   Llama   Lora   Peft   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/ibivibiv/llama3-8b-instruct-code 

Llama3 8B Instruct Code Benchmarks

ARC: 56.4 vs 96.7 (so35)-41.7%
HellaSwag: 78.32 vs 95.3 (gpt4)-17.8%
MMLU: 64.38 vs 88.3 (so35)-27.1%
TruthfulQA: 48.84 vs 59 (gpt4)-17.2%
WinoGrande: 73.8 vs 87.5 (gpt4)-15.7%
GSM8K: 58.07 vs 96.4 (so35)-39.8%
LLME Score: 0.21641
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama3 8B Instruct Code (ibivibiv/llama3-8b-instruct-code)

Llama3 8B Instruct Code Parameters and Internals

Model Type 
text generation
Supported Languages 
en ()
Training Details 
Data Sources:
candenizkocak/code-alpaca-297k
Methodology:
fine-tuning with adapter qlora
Context Length:
4096
Model Architecture:
AutoModelForCausalLM
LLM NameLlama3 8B Instruct Code
Repository 🤗https://huggingface.co/ibivibiv/llama3-8b-instruct-code 
Base Model(s)  Meta Llama 3 8B Instruct   meta-llama/Meta-Llama-3-8B-Instruct
Model Size8b
Required VRAM0.2 GB
Updated2024-12-21
Maintaineribivibiv
Instruction-BasedYes
Model Files  0.2 GB   0.0 GB
Supported Languagesen
Model ArchitectureAdapter
Licensellama3
Is Biasednone
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|end_of_text|>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesq_proj|down_proj|v_proj|gate_proj|up_proj|k_proj|o_proj
LoRA Alpha16
LoRA Dropout0.05
R Param32

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Context / RAM
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...lama 3 1 8B Instruct Orca ORPO0K / 0.1 GB1312
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Vortex20K / 4.4 GB80
FineLlama3.1 8B Instruct Lora0K / 0.2 GB01
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Llama 3 8B Claudstruct V10K / 0.1 GB70
Llama 3 8B Instruct 80K QLoRA0K / 2.2 GB024
...Llama 3 8B Instruct ORPO QLoRA0K / 0.7 GB50
Note: green Score (e.g. "73.2") means that the model is better than ibivibiv/llama3-8b-instruct-code.

Rank the Llama3 8B Instruct Code 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 v20241217
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