Remostart/Plutus_Tutor_model
The Remostart/Plutus_Tutor_model is a 4 billion parameter instruction-tuned causal language model, fine-tuned from Qwen/Qwen3-4B-Instruct-2507. With a context length of 40960 tokens, this model is designed for specific applications, though its exact training data and primary differentiators are not publicly detailed. It leverages the Qwen3 architecture, making it suitable for tasks requiring a compact yet capable language model.
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Plutus_Tutor_model Overview
The Remostart/Plutus_Tutor_model is a 4 billion parameter instruction-tuned language model, building upon the Qwen3-4B-Instruct-2507 architecture developed by Qwen. This model has been fine-tuned, though the specific dataset used for this process is not disclosed in the available documentation. It supports a substantial context length of 40960 tokens, which can be beneficial for tasks requiring extensive input or conversational history.
Key Characteristics
- Base Model: Fine-tuned from Qwen/Qwen3-4B-Instruct-2507.
- Parameter Count: 4 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Features a large context window of 40960 tokens, enabling processing of longer texts.
- Training Details: The model was trained for 2 epochs with a learning rate of 1e-05 and a total batch size of 8, utilizing the ADAMW_TORCH_FUSED optimizer.
Intended Use Cases
While specific intended uses are not detailed, models of this architecture and size are generally suitable for:
- Instruction following and conversational AI.
- Text generation and summarization tasks.
- Applications where a large context window is advantageous for understanding complex queries or documents.