ishikaa/acquisition_student_AS_confidence_numina_qwen14b

TEXT GENERATIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:14.8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 6, 2026Architecture:Transformer Featherless Exclusive Cold

The ishikaa/acquisition_student_AS_confidence_numina_qwen14b is a 14.8 billion parameter language model. This model is a Hugging Face Transformers model that has been automatically pushed to the Hub. Due to limited information in its model card, specific architectural details, training data, and primary differentiators are not provided. Its intended use cases and unique capabilities are currently unspecified.

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Model Overview

The ishikaa/acquisition_student_AS_confidence_numina_qwen14b is a 14.8 billion parameter model hosted on the Hugging Face Hub. This model card has been automatically generated, and as such, many details regarding its development, specific architecture, training methodology, and intended applications are marked as "More Information Needed."

Key Characteristics

  • Model Size: It is a substantial model with 14.8 billion parameters.
  • Context Length: The model supports a context length of 32768 tokens.

Current Limitations

Due to the placeholder nature of the provided model card, specific information on the following is unavailable:

  • Developer and Funding: The entities responsible for its creation and funding are not specified.
  • Model Type and Language(s): The underlying architecture (e.g., decoder-only, encoder-decoder) and the languages it supports are not detailed.
  • Training Data and Procedure: Information regarding the datasets used for training, preprocessing steps, hyperparameters, and training regime is missing.
  • Evaluation Results: No benchmarks or performance metrics are provided.
  • Intended Use Cases: Direct and downstream applications for this model are not outlined.
  • Bias, Risks, and Limitations: While the card notes that users should be aware of potential risks, specific details are not provided.

Users are advised to await further updates to the model card for comprehensive details on its capabilities, performance, and appropriate usage.