ishikaa/acquisition_student_omnimath_diversity_sft_qwen14b

TEXT GENERATIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:14.8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 15, 2026Architecture:Transformer Featherless Exclusive Cold

The ishikaa/acquisition_student_omnimath_diversity_sft_qwen14b model is a 14.8 billion parameter language model. This model is based on the Qwen architecture and has a context length of 32768 tokens. Due to the lack of specific details in its model card, its primary differentiators and specific use cases are not explicitly defined. It is a general-purpose language model, but its specific optimizations or strengths are not detailed.

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Model Overview

The ishikaa/acquisition_student_omnimath_diversity_sft_qwen14b is a 14.8 billion parameter language model built upon the Qwen architecture, featuring a substantial context length of 32768 tokens. This model has been pushed to the Hugging Face Hub as a transformers model.

Key Characteristics

  • Model Type: Qwen-based architecture.
  • Parameters: 14.8 billion parameters.
  • Context Length: Supports a context window of 32768 tokens.

Current Limitations

Based on the provided model card, specific details regarding its development, funding, training data, evaluation metrics, and intended use cases are marked as "More Information Needed." This means that its unique capabilities, performance benchmarks, and specific optimizations are not currently documented. Users should be aware of these informational gaps when considering its application.

Recommendations

Users are advised to exercise caution and conduct thorough testing due to the lack of detailed information on its biases, risks, and limitations. Further recommendations will be available once more comprehensive model details are provided.

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