bijoy0236/ODYSSEUS

TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:3.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Sep 5, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

ODYSSEUS is a 3.1 billion parameter instruction-tuned causal language model developed by bijoy0236. It is finetuned from unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit, leveraging Unsloth for accelerated training. This model offers efficient performance for general instruction-following tasks, benefiting from its optimized training process.

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ODYSSEUS Model Overview

ODYSSEUS is a 3.1 billion parameter language model developed by bijoy0236. It is an instruction-tuned variant, building upon the unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit base model. A key characteristic of ODYSSEUS is its training methodology: it was finetuned using Unsloth and Hugging Face's TRL library, which enabled a 2x faster training process compared to standard methods.

Key Characteristics

  • Base Model: Finetuned from unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit.
  • Parameter Count: 3.1 billion parameters, offering a balance between performance and computational efficiency.
  • Training Efficiency: Utilizes Unsloth for significantly faster training, making it an efficient choice for deployment.
  • Context Length: Supports a context length of 32768 tokens.

Potential Use Cases

ODYSSEUS is suitable for applications requiring a compact yet capable instruction-following model. Its efficient training suggests it could be a good candidate for:

  • General-purpose chatbots and conversational AI.
  • Text generation tasks where a smaller model footprint is advantageous.
  • Applications benefiting from faster inference due to its optimized base and size.

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