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Pythia 6.9B Deduped Synthetic Instruct by lambdalabs

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  Autotrain compatible Dataset:dahoas/synthetic-instr...   En   Endpoints compatible   Gpt neox   Instruct   Pythia   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/lambdalabs/pythia-6.9b-deduped-synthetic-instruct 

Pythia 6.9B Deduped Synthetic Instruct Benchmarks

LLME Score: 0.08628
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Pythia 6.9B Deduped Synthetic Instruct (lambdalabs/pythia-6.9b-deduped-synthetic-instruct)

Pythia 6.9B Deduped Synthetic Instruct Parameters and Internals

Model Type 
Transformer-based Language Model
Use Cases 
Areas:
Research, Commercial Applications
Primary Use Cases:
Text generation
Additional Notes 
Model specifically finetuned on synthetic instruction-following dataset.
Supported Languages 
English (Fluent)
Training Details 
Data Sources:
Dahoas/synthetic-instruct-gptj-pairwise
Methodology:
Finetuning
Training Time:
6 hours
Hardware Used:
8x A100 80GB GPUs
Model Architecture:
Transformer
Input Output 
Accepted Modalities:
text
Output Format:
text
LLM NamePythia 6.9B Deduped Synthetic Instruct
Repository 🤗https://huggingface.co/lambdalabs/pythia-6.9b-deduped-synthetic-instruct 
Model Size6.9b
Required VRAM27.5 GB
Updated2025-02-23
Maintainerlambdalabs
Model Typegpt_neox
Instruction-BasedYes
Model Files  9.9 GB: 1-of-3   9.8 GB: 2-of-3   7.8 GB: 3-of-3
Supported Languagesen
Model ArchitectureGPTNeoXForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.25.1
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50278
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than lambdalabs/pythia-6.9b-deduped-synthetic-instruct.

Rank the Pythia 6.9B Deduped Synthetic Instruct 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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Release v20241227
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