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Seahorse 350M by TitleOS

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Seahorse 350M is an open-source language model by TitleOS. Features: 350m LLM, VRAM: 1.4GB, Context: 2K, License: other, LLM Explorer Score: 0.08.

  Arxiv:2205.01068   Dataset:psmathur/alpaca orca   En   Endpoints compatible   Opt   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TitleOS/Seahorse-350m 

Seahorse 350M Benchmarks

LLME Score: 0.07936
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Seahorse 350M (TitleOS/Seahorse-350m)
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Seahorse 350M Parameters and Internals

Model Type 
text generation
Use Cases 
Limitations:
Potential biases include gender, profession, race and religion.
Training Details 
Data Sources:
psmathur/alpaca_orca
Methodology:
Finetuned on the Orca dataset formatted to the Alpaca style
LLM NameSeahorse 350M
Repository 🤗https://huggingface.co/TitleOS/Seahorse-350m 
Model Size350m
Required VRAM1.4 GB
Updated2026-06-08
MaintainerTitleOS
Model Typeopt
Model Files  0.4 GB: 1-of-4   0.4 GB: 2-of-4   0.4 GB: 3-of-4   0.2 GB: 4-of-4   0.4 GB: 1-of-4   0.4 GB: 2-of-4   0.4 GB: 3-of-4   0.2 GB: 4-of-4
Supported Languagesen
Model ArchitectureOPTForCausalLM
Licenseother
Context Length2048
Model Max Length2048
Transformers Version4.27.0
Beginning of Sentence Token</s>
End of Sentence Token</s>
Unk Token</s>
Vocabulary Size50272
Torch Data Typefloat32
Activation Functionrelu
Errorsreplace

Best Alternatives to Seahorse 350M

Best Alternatives
Context / RAM
Downloads
Likes
Opt Mini Dataset 02K / 0.7 GB50
Facebook Opt 350M SFT Korz142K / 0.7 GB50
Temp Model Sft2K / 1.3 GB70
Opt 350M2K / 0.7 GB143713149
Gpt350 Chat S V0 12K / 0.7 GB80
Gpt350 Chat S V02K / 0.7 GB60
Dadjokes Tuned Opt2K / 1.3 GB122
Pygmalion 350M2K / 1.3 GB121454
Rockyalquimista8882K / 1.3 GB70
Sunday2K / 1.3 GB60
Note: green Score (e.g. "73.2") means that the model is better than TitleOS/Seahorse-350m.

Rank the Seahorse 350M 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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