AntorKumar/rian-chittagong-qwen3b-full

TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:3.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 8, 2026Architecture:Transformer Featherless Exclusive Cold

The AntorKumar/rian-chittagong-qwen3b-full model is a 3.1 billion parameter language model based on the Qwen architecture, developed by AntorKumar. This model is a general-purpose language model, though specific differentiators or fine-tuning details are not provided in its current model card. It is suitable for various natural language processing tasks where a compact yet capable model is required.

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Model Overview

The AntorKumar/rian-chittagong-qwen3b-full is a 3.1 billion parameter language model. While the model card indicates it is a Hugging Face Transformers model, specific details regarding its architecture, training data, or fine-tuning objectives are currently marked as "More Information Needed". This suggests it is a base model or a model whose specific characteristics are yet to be fully documented by its developer, AntorKumar.

Key Characteristics

  • Parameter Count: 3.1 billion parameters, making it a relatively compact model suitable for deployment in resource-constrained environments or for tasks where larger models might be overkill.
  • Context Length: The model supports a context length of 32768 tokens, allowing it to process and generate longer sequences of text.

Intended Use Cases

Given the limited information, this model is likely intended for general natural language processing tasks. Potential applications include:

  • Text generation
  • Text summarization
  • Question answering
  • Chatbot development

Users should be aware that without further details on its training and fine-tuning, its performance on specific tasks may vary. It is recommended to conduct thorough evaluations for any specific use case.

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