Occiglot10b by johannhartmann

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  4-bit   Autotrain compatible Base model:mayflowergmbh/occig... Base model:quantized:mayflower...   Bitsandbytes   Conversational   Endpoints compatible   Generated from trainer   Instruct   Lora   Mistral   Region:us   Safetensors   Sharded   Tensorflow

Occiglot10b Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Occiglot10b (johannhartmann/occiglot10b)

Occiglot10b Parameters and Internals

Model Type 
MistralForCausalLM
Training Details 
Context Length:
2048
LLM NameOcciglot10b
Repository ๐Ÿค—https://huggingface.co/johannhartmann/occiglot10b 
Base Model(s)  Occiglot 10B De En Instruct   mayflowergmbh/occiglot-10b-de-en-instruct
Model Size10b
Required VRAM6.5 GB
Updated2025-02-05
Maintainerjohannhartmann
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   1.5 GB: 2-of-2
Model ArchitectureAutoModelForCausalLM
Is Biasednone
Tokenizer ClassLlamaTokenizer
Padding Token</s>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesdown_proj|o_proj|v_proj|up_proj|gate_proj|q_proj|k_proj
LoRA Alpha32
LoRA Dropout0.05
R Param64

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Note: green Score (e.g. "73.2") means that the model is better than johannhartmann/occiglot10b.

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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 v20241227