AnkitBirGurung/Helpful_NEMO_12B_SFT_Further

TEXT GENERATIONConcurrent Unit Cost:1Model Size:12BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 14, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

AnkitBirGurung/Helpful_NEMO_12B_SFT_Further is a 12 billion parameter Mistral-based language model, developed by AnkitBirGurung, with a 32768 token context length. This model is a further fine-tuned version of BUSINESS_PSYCHOLOGY_NEMO_12_PLATINUM_SFT_FURTHER, optimized for specific applications through efficient training with Unsloth and Huggingface's TRL library. It is designed for tasks requiring a robust understanding and generation of text, leveraging its large parameter count and extended context window.

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Overview

AnkitBirGurung/Helpful_NEMO_12B_SFT_Further is a 12 billion parameter language model, developed by AnkitBirGurung, built upon the Mistral architecture. It features a substantial context length of 32768 tokens, enabling it to process and generate longer, more coherent texts. This model represents a further fine-tuned iteration of the previously released BUSINESS_PSYCHOLOGY_NEMO_12_PLATINUM_SFT_FURTHER.

Key Capabilities

  • Efficient Fine-tuning: The model was fine-tuned using Unsloth and Huggingface's TRL library, which allowed for a 2x faster training process.
  • Extended Context Window: With a 32768 token context length, it can handle complex queries and generate detailed responses, maintaining context over longer interactions.
  • Mistral-based Architecture: Leverages the robust and efficient architecture of Mistral models, known for their strong performance in various language understanding and generation tasks.

Good For

  • Applications requiring a model with a large context window for processing extensive documents or conversations.
  • Tasks benefiting from a model that has undergone specific, efficient fine-tuning for improved performance in particular domains.
  • Developers looking for a powerful 12B parameter model that balances performance with optimized training methodologies.