ishikaa/acquisition_student_AS_confidence_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 25, 2026Architecture:Transformer Featherless Exclusive Cold

The ishikaa/acquisition_student_AS_confidence_alpaca_qwen3b_5000 is a 3.1 billion parameter language model with a 32768 token context length. This model is based on the Qwen architecture, likely fine-tuned for specific tasks given its name, and is designed for general language understanding and generation. Its primary application would be in scenarios requiring a compact yet capable model for various NLP tasks.

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Model Overview

The ishikaa/acquisition_student_AS_confidence_alpaca_qwen3b_5000 is a 3.1 billion parameter language model built upon the Qwen architecture. It features a substantial context window of 32768 tokens, enabling it to process and generate longer sequences of text. While specific training details and differentiators are not explicitly provided in the model card, the naming convention suggests it may be a fine-tuned variant, potentially optimized for tasks related to "acquisition student confidence" or similar domains.

Key Capabilities

  • General Language Understanding: Capable of processing and interpreting natural language inputs.
  • Text Generation: Can generate coherent and contextually relevant text based on prompts.
  • Extended Context Handling: Benefits from a 32768 token context length, suitable for tasks requiring extensive input or output.

Potential Use Cases

  • Text Summarization: Handling longer documents due to its large context window.
  • Question Answering: Answering queries based on provided text.
  • Content Creation: Generating various forms of written content.
  • Exploratory NLP Tasks: Serving as a base model for further fine-tuning on specific datasets, especially where the "acquisition student confidence" aspect might be relevant.

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