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Phi 3 Mini 4K Instruct Q4 by bongodongo

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  4-bit   Autotrain compatible   Bitsandbytes   Conversational   Custom code   Endpoints compatible   Instruct   Phi3   Q4   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/bongodongo/phi-3-mini-4k-instruct-q4 

Phi 3 Mini 4K Instruct Q4 Benchmarks

LLME Score: 0.19615
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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Phi 3 Mini 4K Instruct Q4 Parameters and Internals

Model Type 
quantized, causal language model
Additional Notes 
This version utilizes a 4-bit quantized model configuration using BitsAndBytesConfig with features such as double quantization and nf4 quant type for reduced computation requirements.
LLM NamePhi 3 Mini 4K Instruct Q4
Repository 🤗https://huggingface.co/bongodongo/phi-3-mini-4k-instruct-q4 
Base Model(s)  CitrusBoy/FinetunedModelV2.0   CitrusBoy/FinetunedModelV2.0
Model Size2.1b
Required VRAM2.3 GB
Updated2024-12-03
Maintainerbongodongo
Model Typephi3
Instruction-BasedYes
Model Files  2.3 GB
Quantization Typeq4
Model ArchitecturePhi3ForCausalLM
Context Length4096
Model Max Length4096
Transformers Version4.40.0
Tokenizer ClassLlamaTokenizer
Padding Token<|endoftext|>
Vocabulary Size32064
Torch Data Typefloat16
Phi 3 Mini 4K Instruct Q4 (bongodongo/phi-3-mini-4k-instruct-q4)

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Note: green Score (e.g. "73.2") means that the model is better than bongodongo/phi-3-mini-4k-instruct-q4.

Rank the Phi 3 Mini 4K Instruct Q4 Capabilities

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Instruction Following and Task Automation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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