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Tigerbot 7B Sft V1 by TigerResearch

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  Autotrain compatible   Bloom   Endpoints compatible   Pytorch   Region:us   Sharded

Tigerbot 7B Sft V1 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: 0.12699
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 Parameters and Internals

LLM NameTigerbot 7B Sft V1
Repository 🤗https://huggingface.co/TigerResearch/tigerbot-7b-sft-v1 
Model Size7b
Required VRAM16.2 GB
Updated2024-09-19
MaintainerTigerResearch
Model Typebloom
Model Files  10.0 GB: 1-of-2   6.2 GB: 2-of-2
Model ArchitectureBloomForCausalLM
Licenseapache-2.0
Model Max Length1024
Transformers Version4.28.1
Tokenizer ClassBloomTokenizer
Padding Token<pad>
Vocabulary Size250682
Torch Data Typefloat16
Tigerbot 7B Sft V1 (TigerResearch/tigerbot-7b-sft-v1)

Quantized Models of the Tigerbot 7B Sft V1

Model
Likes
Downloads
VRAM
Tigerbot 7B Sft V1 4bit6155 GB

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Bloom Xp30K / 32.4 GB60
Vietcuna 7B V30K / 14.2 GB728
Note: green Score (e.g. "73.2") means that the model is better than TigerResearch/tigerbot-7b-sft-v1.

Rank the Tigerbot 7B Sft V1 Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
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Text Summarization and Feature Extraction  
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Multi-Language Support and Translation  

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Release v2024072803
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