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Pythia 6.9B HC3 by pszemraj

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  Assistant   Autotrain compatible Base model:eleutherai/pythia-6... Base model:finetune:eleutherai...   Chatgpt Dataset:pszemraj/hc3-textgen-q...   Generated from trainer   Gpt neox   Hc3   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/pszemraj/pythia-6.9b-HC3 

Pythia 6.9B HC3 Benchmarks

ARC: 36.52 vs 96.7 (so35)-62.2%
HellaSwag: 61.76 vs 95.3 (gpt4)-35.2%
MMLU: 26.94 vs 88.3 (so35)-69.5%
TruthfulQA: 45.05 vs 59 (gpt4)-23.6%
WinoGrande: 60.77 vs 87.5 (gpt4)-30.5%
LLME Score: 0.10518
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 HC3 (pszemraj/pythia-6.9b-HC3)
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Pythia 6.9B HC3 Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
research
Applications:
exploration into comparing RLHF tuning vs. 'guided'/specific tuning on 'quality' datasets
Limitations:
Not trained/fine-tuned with RLHF., Will not be as helpful/generalizable/safe as chatGPT., Model is ~30x smaller than chatGPT.
Additional Notes 
The model was not trained with Reinforcement Learning through Human Feedback (RLHF) and focuses on generating high-quality answers akin to what humans would desire.
Training Details 
Data Sources:
pszemraj/HC3-textgen-qa
Methodology:
fine-tuning
Input Output 
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Contrastive search with top_k=4 and penalty_alpha=0.6 is used for generation.
Release Notes 
Version:
pythia-6.9b-hc3-qa-assistant
Notes:
Tested on causal language modeling with a training loss of 1.2598, and validated with a loss of 1.2372 and an accuracy of 0.6769.
LLM NamePythia 6.9B HC3
Repository 🤗https://huggingface.co/pszemraj/pythia-6.9b-HC3 
Base Model(s)  EleutherAI/pythia-6.9b-deduped   EleutherAI/pythia-6.9b-deduped
Model Size6.9b
Required VRAM27.7 GB
Updated2025-09-23
Maintainerpszemraj
Model Typegpt_neox
Model Files  3.8 GB: 1-of-8   3.8 GB: 2-of-8   4.0 GB: 3-of-8   3.9 GB: 4-of-8   3.8 GB: 5-of-8   3.8 GB: 6-of-8   3.8 GB: 7-of-8   0.8 GB: 8-of-8   3.8 GB: 1-of-8   3.8 GB: 2-of-8   4.0 GB: 3-of-8   3.9 GB: 4-of-8   3.8 GB: 5-of-8   3.8 GB: 6-of-8   3.8 GB: 7-of-8   0.8 GB: 8-of-8
Model ArchitectureGPTNeoXForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.27.0.dev0
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50432
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than pszemraj/pythia-6.9b-HC3.

Rank the Pythia 6.9B HC3 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  
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