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Chat Opt 350M Reward Deepspeed by AdamG012

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  Autotrain compatible   Chatgpt   Dataset:dahoas/full-hh-rlhf Dataset:dahoas/synthetic-instr... Dataset:openai/webgpt comparis...   Dataset:stanfordnlp/shp Dataset:yitingxie/rlhf-reward-...   Deepspeed   En   Endpoints compatible   Instruct   Opt   Pytorch   Region:us   Reward-model
Model Card on HF 🤗: https://huggingface.co/AdamG012/chat-opt-350m-reward-deepspeed 

Chat Opt 350M Reward Deepspeed Benchmarks

LLME Score: 0.07782
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Chat Opt 350M Reward Deepspeed (AdamG012/chat-opt-350m-reward-deepspeed)
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Chat Opt 350M Reward Deepspeed Parameters and Internals

Model Type 
reward-model
Use Cases 
Areas:
research, commercial applications
Additional Notes 
The model consists of the second step of a modified pipeline for training ChatGPT models and utilizes DeepSpeed frameworks for efficient resource use.
Training Details 
Data Sources:
Dahoas/full-hh-rlhf, Dahoas/synthetic-instruct-gptj-pairwise, yitingxie/rlhf-reward-datasets, openai/webgpt_comparisons, stanfordnlp/SHP
Methodology:
The training process involves a three-step pipeline including supervised fine tuning, reward model fine tuning, and reinforcement learning from human feedback (RLHF).
Context Length:
2048
Model Architecture:
OPT with 350M parameters, FFN dimensions 4096, Hidden size 1024, Attention heads 16, and Hidden layers 24.
LLM NameChat Opt 350M Reward Deepspeed
Repository 🤗https://huggingface.co/AdamG012/chat-opt-350m-reward-deepspeed 
Model Size350m
Required VRAM0.7 GB
Updated2025-09-23
MaintainerAdamG012
Model Typeopt
Instruction-BasedYes
Model Files  0.7 GB
Supported Languagesen
Model ArchitectureOPTForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.29.0.dev0
Vocabulary Size50272
Torch Data Typefloat16
Activation Functionrelu

Best Alternatives to Chat Opt 350M Reward Deepspeed

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Note: green Score (e.g. "73.2") means that the model is better than AdamG012/chat-opt-350m-reward-deepspeed.

Rank the Chat Opt 350M Reward Deepspeed 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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