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Opt 2.7B Realtime Chat by AbrahamSanders

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  Autotrain compatible   Endpoints compatible   Opt   Pytorch   Region:us   Sharded   Tensorboard
Model Card on HF 🤗: https://huggingface.co/AbrahamSanders/opt-2.7b-realtime-chat 

Opt 2.7B Realtime Chat Benchmarks

LLME Score: 0.05414
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Opt 2.7B Realtime Chat (AbrahamSanders/opt-2.7b-realtime-chat)
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Opt 2.7B Realtime Chat Parameters and Internals

Model Type 
causal language modeling
Training Details 
Data Sources:
TalkBank CABank collection, CABNC, CallFriend English (N), CallFriend English (S), CallHome English, GCSAusE, ISL, MICASE, SCoSE
Input Output 
Input Format:
Spoken dialogue sequence prefixed with participant information and notations.
Accepted Modalities:
text
LLM NameOpt 2.7B Realtime Chat
Repository 🤗https://huggingface.co/AbrahamSanders/opt-2.7b-realtime-chat 
Model Size2.7b
Required VRAM11.1 GB
Updated2025-09-14
MaintainerAbrahamSanders
Model Typeopt
Model Files  10.0 GB: 1-of-2   1.1 GB: 2-of-2
Model ArchitectureOPTForCausalLM
Licensecc-by-3.0
Context Length2048
Model Max Length2048
Transformers Version4.24.0
Tokenizer ClassGPT2Tokenizer
Beginning of Sentence Token</s>
End of Sentence Token</s>
Unk Token</s>
Vocabulary Size50265
Torch Data Typefloat32
Activation Functionrelu
Errorsreplace

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Context / RAM
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LLmRa 2.7B2K / 10.6 GB6421
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Opt 2.7B Realtime Chat V22K / 11.1 GB50
LongForm OPT 2.7B2K / 5.3 GB73
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Opt 2.7B AWQ2K / 1.6 GB80
Note: green Score (e.g. "73.2") means that the model is better than AbrahamSanders/opt-2.7b-realtime-chat.

Rank the Opt 2.7B Realtime Chat 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 v20241124
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