SauerkrautLM 7B LaserChat by VAGOsolutions

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  Augmentation   Autotrain compatible   Conversational   De   Dpo   En   Endpoints compatible   English   Finetuned   German   Laser   Mistral   Region:us   Safetensors   Sft   Sharded   Tensorflow

SauerkrautLM 7B LaserChat Benchmarks

SauerkrautLM 7B LaserChat (VAGOsolutions/SauerkrautLM-7b-LaserChat)

SauerkrautLM 7B LaserChat Parameters and Internals

Model Type 
text-generation, finetuned
Use Cases 
Limitations:
Certain language formulations may be incorrect
Additional Notes 
Novel training strategies effectively prevent language models from forgetting previously acquired knowledge
Supported Languages 
German (improved skills), English (supported)
Training Details 
Data Sources:
SFT-Sauerkraut dataset, DPO dataset
Methodology:
Fine-tuned with SFT; aligned with DPO; novel training technique using partial model freezing and LaserRMT optimization
LLM NameSauerkrautLM 7B LaserChat
Repository ๐Ÿค—https://huggingface.co/VAGOsolutions/SauerkrautLM-7b-LaserChat 
Model Size7b
Required VRAM14.4 GB
Updated2025-02-04
MaintainerVAGOsolutions
Model Typemistral
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Supported Languagesen de
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32002
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than VAGOsolutions/SauerkrautLM-7b-LaserChat.

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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  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227