The ishikaa/influence_metamath_qwen2.5-3b_confidence_repeat_regularized_2k_scaled model is a 3.1 billion parameter language model based on the Qwen2.5 architecture, with a context length of 32768 tokens. This model's specific characteristics and primary differentiators are not detailed in the provided README, which indicates "More Information Needed" across all key sections. Its intended use cases and unique capabilities are currently undefined.
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Overview
This model, ishikaa/influence_metamath_qwen2.5-3b_confidence_repeat_regularized_2k_scaled, is a 3.1 billion parameter language model built upon the Qwen2.5 architecture, supporting a context length of 32768 tokens. The provided model card indicates that detailed information regarding its development, specific model type, language support, and fine-tuning origins is currently unavailable.
Key Capabilities
- Architecture: Based on the Qwen2.5 model family.
- Parameter Count: Features 3.1 billion parameters.
- Context Length: Supports a substantial context window of 32768 tokens.
Current Limitations and Information Gaps
As per the model card, critical details regarding the model's intended uses, direct applications, downstream potential, out-of-scope uses, and any inherent biases, risks, or limitations are not yet specified. Information on training data, procedures, evaluation metrics, and results is also marked as "More Information Needed." Users should be aware of these significant information gaps when considering this model.