ishikaa/acquisition_student_randomselfgen_alpaca_qwen3b_5000

TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:3.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Sep 26, 2026Architecture:Transformer Featherless Exclusive Cold

The ishikaa/acquisition_student_randomselfgen_alpaca_qwen3b_5000 model is a 3.1 billion parameter language model. Based on the Qwen architecture, it is part of a series of models developed by ishikaa. This model is likely a result of an acquisition or student project, potentially exploring self-generation techniques with an Alpaca-style instruction following dataset. Its specific differentiators and primary use cases are not detailed in the provided information.

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Model Overview

This model, ishikaa/acquisition_student_randomselfgen_alpaca_qwen3b_5000, is a 3.1 billion parameter language model. While specific details regarding its architecture, training, and intended use are marked as "More Information Needed" in its model card, its name suggests it is likely based on the Qwen architecture and may have been fine-tuned using an Alpaca-style dataset, potentially incorporating random self-generation techniques.

Key Characteristics

  • Parameter Count: 3.1 billion parameters.
  • Context Length: Supports a context length of 32768 tokens.
  • Origin: Developed by ishikaa, possibly as part of an acquisition or student project.

Limitations and Recommendations

Due to the lack of detailed information in the model card, specific biases, risks, and limitations are currently unknown. Users are advised to exercise caution and conduct thorough evaluations before deploying this model in any application. Further information is needed to provide comprehensive recommendations for its use.

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