Codestral 22B V0.1 EXL2 5.0bpw by bullerwins

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  5-bit   Autotrain compatible   Code   Exl2   Mistral   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Codestral 22B V0.1 EXL2 5.0bpw Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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Codestral 22B V0.1 EXL2 5.0bpw Parameters and Internals

Model Type 
code generation, text completion
Use Cases 
Areas:
research, software development
Primary Use Cases:
code generation, code explanation, software development add-ons
Limitations:
Does not have any moderation mechanisms
Additional Notes 
Codestral-22B-v0.1 is recommended to be used with mistral_inference for optimal performance.
Training Details 
Methodology:
exllamav2 0.1.1
LLM NameCodestral 22B V0.1 EXL2 5.0bpw
Repository ๐Ÿค—https://huggingface.co/bullerwins/Codestral-22B-v0.1-exl2_5.0bpw 
Model Size22b
Required VRAM14.2 GB
Updated2025-06-09
Maintainerbullerwins
Model Typemistral
Model Files  8.6 GB: 1-of-2   5.6 GB: 2-of-2
Supported Languagescode
Quantization Typeexl2
Model ArchitectureMistralForCausalLM
LicenseMNPL-0.1
Context Length32768
Model Max Length32768
Transformers Version4.40.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32768
Torch Data Typebfloat16
Codestral 22B V0.1 EXL2 5.0bpw (bullerwins/Codestral-22B-v0.1-exl2_5.0bpw)

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Note: green Score (e.g. "73.2") means that the model is better than bullerwins/Codestral-22B-v0.1-exl2_5.0bpw.

Rank the Codestral 22B V0.1 EXL2 5.0bpw 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 v20241124