torchtorchkimtorch/up_model_score_specialized
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Apr 29, 2026Architecture:Transformer Cold
The torchtorchkimtorch/up_model_score_specialized is a 7 billion parameter causal language model. It is specifically designed for inference using the lm-eval-harness ARC basic prompt format (Question: {q}\nAnswer: {a}). This model is optimized for tasks requiring structured question-answering based on this specific prompt format.
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Model Overview
The torchtorchkimtorch/up_model_score_specialized is a 7 billion parameter causal language model. Its primary characteristic is its optimization for a specific inference prompt format, making it suitable for tasks that adhere to this structure.
Key Capabilities
- Specialized Prompt Format: Designed to work efficiently with the
lm-eval-harnessARC basic prompt format:Question: {q}\nAnswer: {a}. - Causal Language Modeling: Functions as a causal language model, generating text based on preceding tokens.
Good For
- Structured Question Answering: Ideal for applications where questions and answers follow the specified ARC prompt format.
- Benchmarking with lm-eval-harness: Directly compatible with evaluation frameworks that utilize the ARC prompt structure for assessment.
- Specific Inference Tasks: Best suited for use cases that can leverage its specialized prompt handling for consistent and predictable output.