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Ct2fast Pythia 12B Sft V8 7K Steps by michaelfeil

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  Ctranslate2   En   Endpoints compatible   Float16 - sft   Int8   Region:us
Model Card on HF 🤗: https://huggingface.co/michaelfeil/ct2fast-pythia-12b-sft-v8-7k-steps 

Ct2fast Pythia 12B Sft V8 7K Steps Benchmarks

LLME Score: 0.08353
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Ct2fast Pythia 12B Sft V8 7K Steps (michaelfeil/ct2fast-pythia-12b-sft-v8-7k-steps)
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Ct2fast Pythia 12B Sft V8 7K Steps Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
research, commercial applications
Additional Notes 
Fast inference with Ctranslate2 using int8 and float16 quantization.
Supported Languages 
en (proficient)
Training Details 
Data Sources:
oasst_export, vicuna, dolly15k, grade_school_math_instructions, code_alpaca, red_pajama, wizardlm_70k, poem_instructions
Data Volume:
multiple datasets with varying val_split and fraction parameters
Methodology:
supervised fine-tuning
Context Length:
2048
Model Architecture:
Derived from OpenAssistant/pythia-12b-pre-v8-12.5k-steps
Input Output 
Accepted Modalities:
text
Performance Tips:
Use 'device="cuda", compute_type="int8_float16"' for optimal CUDA performance.
LLM NameCt2fast Pythia 12B Sft V8 7K Steps
Repository 🤗https://huggingface.co/michaelfeil/ct2fast-pythia-12b-sft-v8-7k-steps 
Model Size12b
Required VRAM23.7 GB
Updated2025-10-14
Maintainermichaelfeil
Model Files  23.7 GB
Supported Languagesen
Model ArchitectureAutoModel
Licenseapache-2.0
Tokenizer ClassGPTNeoXTokenizer

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Note: green Score (e.g. "73.2") means that the model is better than michaelfeil/ct2fast-pythia-12b-sft-v8-7k-steps.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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