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Opt Peter 2.7B by pszemraj

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Opt Peter 2.7B is an open-source language model by pszemraj. Features: 2.7b LLM, VRAM: 10.6GB, Context: 2K, License: other|apache-2.0, LLM Explorer Score: 0.01.

  Ai-msgbot   Base model:facebook/opt-2.7b Base model:finetune:facebook/o...   Chatbot   Dialogue   Doi:10.57967/hf/0233   Endpoints compatible   Generated from trainer   Non-commercial   Opt   Pytorch   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/pszemraj/opt-peter-2.7B 

Opt Peter 2.7B Benchmarks

LLME Score: 0.01488
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Opt Peter 2.7B (pszemraj/opt-peter-2.7B)
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Opt Peter 2.7B Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
non-commercial
Applications:
dialogue, conversational applications, chatbot
Primary Use Cases:
text generation
Limitations:
Model is too large for API use, require high RAM
Considerations:
Use responsibly, as it is a fine-tuned version of the base model.
Additional Notes 
Sharded checkpoint available due to large size of model file.
Training Details 
Data Sources:
WhatsApp text messages, iMessages
Data Volume:
about 80k messages
Methodology:
Fine-tuning
LLM NameOpt Peter 2.7B
Repository 🤗https://huggingface.co/pszemraj/opt-peter-2.7B 
Base Model(s)  facebook/opt-2.7b   facebook/opt-2.7b
Model Size2.7b
Required VRAM10.6 GB
Updated2026-03-18
Maintainerpszemraj
Model Typeopt
Model Files  10.6 GB   10.6 GB   0.0 GB
Model ArchitectureOPTForCausalLM
Licenseother|apache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.19.2
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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OPT 2.7B Nerys V22K / 5.3 GB6236
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LongForm OPT 2.7B2K / 5.3 GB103
Opt 2.7B Wikitext22K / 11.1 GB110
Opt 2.7B Realtime Chat2K / 11.1 GB22
Opt 2.7B AWQ2K / 1.6 GB70
Note: green Score (e.g. "73.2") means that the model is better than pszemraj/opt-peter-2.7B.

Rank the Opt Peter 2.7B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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