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ECeLLM M by NingLab

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  Autotrain compatible   Conversational   Dataset:ninglab/ecinstruct   Endpoints compatible   Instruct   Mistral   Region:us   Safetensors   Sharded   Tensorflow

ECeLLM M Benchmarks

LLME Score: 0.19998
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

ECeLLM M Parameters and Internals

LLM NameECeLLM M
Repository 🤗https://huggingface.co/NingLab/eCeLLM-M 
Model Size7b
Required VRAM14.4 GB
Updated2024-10-22
MaintainerNingLab
Model Typemistral
Instruction-BasedYes
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Model ArchitectureMistralForCausalLM
Licensecc-by-4.0
Context Length32768
Model Max Length32768
Transformers Version4.38.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16
ECeLLM M (NingLab/eCeLLM-M)

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XLAM 7B R32K / 14.4 GB2138825
Note: green Score (e.g. "73.2") means that the model is better than NingLab/eCeLLM-M.

Rank the ECeLLM M 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 v2024072803
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