torchtorchkimtorch/up_model
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Apr 29, 2026Architecture:Transformer Cold
The torchtorchkimtorch/up_model is a 7 billion parameter causal language model designed for general text generation tasks. It is specifically optimized for inference using the lm-eval-harness ARC basic prompt format, making it suitable for question-answering and reasoning applications. This model provides a foundational base for various natural language processing tasks.
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Model Overview
The torchtorchkimtorch/up_model is a 7 billion parameter causal language model. It is designed for general text generation and is particularly noted for its compatibility with the lm-eval-harness ARC basic prompt format during inference. This makes it well-suited for tasks requiring structured question-answering.
Key Capabilities
- Causal Language Modeling: Generates coherent and contextually relevant text based on a given prompt.
- Optimized for ARC Prompt Format: Specifically configured to work efficiently with the "Question: {q}\nAnswer: {a}" prompt structure, facilitating its use in question-answering and reasoning benchmarks.
- Standard Hugging Face Integration: Easily loadable and usable with the
transformerslibrary for straightforward deployment and experimentation.
Good For
- Question Answering: Ideal for applications where questions are posed and direct answers are expected, especially when formatted according to the ARC prompt style.
- General Text Generation: Can be used for various generative tasks, including content creation, summarization, and conversational AI.
- Research and Development: Provides a solid base for further fine-tuning or experimentation in natural language processing.