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Yi Coder 9B Chat Instruct TIES by BenevolenceMessiah

 »  All LLMs  »  BenevolenceMessiah  »  Yi Coder 9B Chat Instruct TIES   URL Share it on

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  Merged Model   Arxiv:2306.01708   Arxiv:2403.04652   Autotrain compatible   Base model:01-ai/yi-coder-9b Base model:01-ai/yi-coder-9b-c...   Codegen   Endpoints compatible   Instruct   Llama   Region:us   Safetensors   Sharded   Tensorflow

Yi Coder 9B Chat Instruct TIES Benchmarks

LLME Score: 0.23552
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Yi Coder 9B Chat Instruct TIES Parameters and Internals

Model Type 
chat, code generation
Use Cases 
Areas:
commercial applications, research
Applications:
programming assistance, code generation, software development
Primary Use Cases:
writing algorithms, code refactoring, understanding programming languages
Additional Notes 
The model is part of the Yi-Coder series known for strong coding performance with under 10 billion parameters and long-context understanding.
Supported Languages 
java (proficient), markdown (proficient), python (proficient), php (proficient), javascript (proficient), c++ (proficient), c# (proficient), c (proficient), typescript (proficient), html (proficient), go (proficient), java_server_pages (proficient), dart (proficient), objective-c (proficient), kotlin (proficient), tex (proficient), swift (proficient), ruby (proficient), sql (proficient), rust (proficient), css (proficient), yaml (proficient), matlab (proficient), lua (proficient), json (proficient), shell (proficient), visual_basic (proficient), scala (proficient), rmarkdown (proficient), pascal (proficient), fortran (proficient), haskell (proficient), assembly (proficient), perl (proficient), julia (proficient), cmake (proficient), groovy (proficient), ocaml (proficient), powershell (proficient), elixir (proficient), clojure (proficient), makefile (proficient), coffeescript (proficient), erlang (proficient), lisp (proficient), toml (proficient), batchfile (proficient), cobol (proficient), dockerfile (proficient), r (proficient), prolog (proficient), verilog (proficient)
Training Details 
Methodology:
TIES merge method
Context Length:
128000
Input Output 
Input Format:
[JSON] chat messages with roles system, user
Accepted Modalities:
text
Output Format:
Text responses
Performance Tips:
Use a CUDA-enabled device for optimal performance.
LLM NameYi Coder 9B Chat Instruct TIES
Repository 🤗https://huggingface.co/BenevolenceMessiah/Yi-Coder-9B-Chat-Instruct-TIES 
Base Model(s)  Yi Coder 9B Chat   Yi Coder 9B   01-ai/Yi-Coder-9B-Chat   01-ai/Yi-Coder-9B
Merged ModelYes
Model Size9b
Required VRAM17.7 GB
Updated2024-11-22
MaintainerBenevolenceMessiah
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-4   4.9 GB: 2-of-4   5.0 GB: 3-of-4   2.8 GB: 4-of-4
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.44.1
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size64000
Torch Data Typefloat16
Yi Coder 9B Chat Instruct TIES (BenevolenceMessiah/Yi-Coder-9B-Chat-Instruct-TIES)

Rank the Yi Coder 9B Chat Instruct TIES 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 v20241110
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