FinaPolat/RAISED_Mistral-Nemo_SFT

TEXT GENERATIONConcurrency Cost:1Model Size:12BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Apr 15, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

FinaPolat/RAISED_Mistral-Nemo_SFT is a 12 billion parameter Mistral-Nemo instruction-tuned model developed by FinaPolat. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. It is designed for general language tasks, leveraging its Mistral architecture and efficient training methodology.

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Model Overview

FinaPolat/RAISED_Mistral-Nemo_SFT is a 12 billion parameter instruction-tuned language model developed by FinaPolat. It is based on the Mistral-Nemo architecture and was fine-tuned from the unsloth/mistral-nemo-instruct-2407-bnb-4bit model.

Key Characteristics

  • Efficient Training: This model was trained significantly faster, achieving 2x speed improvements by utilizing the Unsloth library in conjunction with Huggingface's TRL library.
  • Parameter Count: With 12 billion parameters, it offers a balance between performance and computational efficiency.
  • Context Length: The model supports a context length of 32768 tokens, allowing it to process and generate longer sequences of text.

Potential Use Cases

This model is suitable for a variety of general natural language processing tasks, including:

  • Instruction-following and conversational AI.
  • Text generation and summarization.
  • Question answering.
  • Applications where efficient training and a substantial context window are beneficial.

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