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Portfolio Query Llama 3.2 3B V3 Cot by Bharatdeep-H

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  4bit   Autotrain compatible   Conversational   En   Endpoints compatible   Instruct   Llama   Pytorch   Quantized   Region:us   Sft   Sharded   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/Bharatdeep-H/portfolio-query-llama-3.2-3b-v3-cot 

Portfolio Query Llama 3.2 3B V3 Cot Benchmarks

LLME Score: 0.25157
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Portfolio Query Llama 3.2 3B V3 Cot (Bharatdeep-H/portfolio-query-llama-3.2-3b-v3-cot)

Portfolio Query Llama 3.2 3B V3 Cot Parameters and Internals

Model Type 
text-generation
Additional Notes 
This model was trained 2x faster using the Unsloth and Huggingface's TRL library.
Supported Languages 
en (unknown)
LLM NamePortfolio Query Llama 3.2 3B V3 Cot
Repository 🤗https://huggingface.co/Bharatdeep-H/portfolio-query-llama-3.2-3b-v3-cot 
Base Model(s)  unsloth/llama-3.2-3b-instruct-bnb-4bit   unsloth/llama-3.2-3b-instruct-bnb-4bit
Model Size3b
Required VRAM6.5 GB
Updated2024-12-26
MaintainerBharatdeep-H
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   1.5 GB: 2-of-2
Supported Languagesen
Quantization Type4bit
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.44.2
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|finetune_right_pad_id|>
Vocabulary Size128256
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than Bharatdeep-H/portfolio-query-llama-3.2-3b-v3-cot.

Rank the Portfolio Query Llama 3.2 3B V3 Cot 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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