digotetso/deepseek-r1-7b-csi131-csi132-tutor

TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:Mar 18, 2026Architecture:Transformer Cold

The digotetso/deepseek-r1-7b-csi131-csi132-tutor is a 7.6 billion parameter language model based on the DeepSeek-R1 architecture, designed for general language understanding and generation tasks. This model is a fine-tuned variant, likely optimized for specific instructional or tutoring applications, leveraging its substantial parameter count for robust performance. Its 32768-token context window enables processing of extensive inputs, making it suitable for complex conversational or document-based tasks.

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Model Overview

This model, digotetso/deepseek-r1-7b-csi131-csi132-tutor, is a 7.6 billion parameter language model. It is based on the DeepSeek-R1 architecture and has been pushed to the Hugging Face Hub as a 🤗 transformers model. While specific details regarding its development, funding, and training data are not provided in the current model card, its name suggests a focus on instructional or tutoring applications.

Key Characteristics

  • Parameter Count: 7.6 billion parameters, indicating a powerful model capable of handling complex language tasks.
  • Context Length: Features a 32768-token context window, allowing for the processing and generation of long sequences of text.
  • Architecture: Built upon the DeepSeek-R1 model family.

Potential Use Cases

Given its architecture and parameter size, this model is likely suitable for a variety of natural language processing tasks, particularly those requiring a deep understanding of context and the ability to generate coherent and relevant responses. The 'tutor' suffix in its name implies potential optimization for:

  • Educational applications: Assisting with learning, explaining concepts, or generating study materials.
  • Instructional dialogues: Engaging in question-answering or guided learning scenarios.
  • General text generation: Creating diverse forms of content, from summaries to creative writing, within its extensive context window.