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Tigerbot 7B Sft V1 4bit by TigerResearch

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  4bit   Autotrain compatible   Bloom   Endpoints compatible   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/TigerResearch/tigerbot-7b-sft-v1-4bit 

Tigerbot 7B Sft V1 4bit Benchmarks

ARC: 58.4 vs 96.7 (so35)-39.6%
HellaSwag: 59.8 vs 95.3 (gpt4)-37.3%
MMLU: 31.4 vs 88.3 (so35)-64.4%
GSM8K: 12.4 vs 96.4 (so35)-87.1%
OpenCompas: 39 vs 73.3 (gpt4)-46.8%
Exam: 38.5 vs 77.2 (gpt4)-50.1%
Language: 39.6 vs 62 (gpt4)-36.1%
Knowledge: 41.4 vs 73.5 (gpt4)-43.7%
Understand: 42.1 vs 70 (gpt4)-39.9%
Reasoning: 37.1 vs 74.4 (gpt4)-50.1%
LLME Score: 0.10548
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Tigerbot 7B Sft V1 4bit (TigerResearch/tigerbot-7b-sft-v1-4bit)

Tigerbot 7B Sft V1 4bit Parameters and Internals

Model Type 
LLM, GPTQ version
Additional Notes 
This is a 4-bit GPTQ version of the Tigerbot 7B sft, quantized to 4bit using a specific method.
LLM NameTigerbot 7B Sft V1 4bit
Repository 🤗https://huggingface.co/TigerResearch/tigerbot-7b-sft-v1-4bit 
Base Model(s)  Tigerbot 7B Sft V1   TigerResearch/tigerbot-7b-sft-v1
Model Size7b
Required VRAM5.2 GB
Updated2025-02-22
MaintainerTigerResearch
Model Typebloom
Model Files  5.2 GB
Quantization Type4bit
Model ArchitectureBloomForCausalLM
Licenseapache-2.0
Model Max Length1024
Transformers Version4.27.0.dev0
Tokenizer ClassBloomTokenizer
Padding Token<pad>
Vocabulary Size250682
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than TigerResearch/tigerbot-7b-sft-v1-4bit.

Rank the Tigerbot 7B Sft V1 4bit 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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