whotao1766/llama3-sft-rag-model

TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 25, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The whotao1766/llama3-sft-rag-model is an 8 billion parameter Llama 3.1 model, fine-tuned from unsloth/llama-3.1-8b-unsloth-bnb-4bit. Developed by whotao1766, this model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster fine-tuning. It is designed for general language understanding and generation tasks, leveraging its efficient training methodology.

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Model Overview

The whotao1766/llama3-sft-rag-model is an 8 billion parameter Llama 3.1-based language model, fine-tuned by whotao1766. It originates from the unsloth/llama-3.1-8b-unsloth-bnb-4bit base model, indicating its foundation in the Llama 3.1 architecture.

Key Characteristics

  • Architecture: Llama 3.1
  • Parameters: 8 billion
  • Training Efficiency: This model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
  • License: Distributed under the Apache-2.0 license.

Use Cases

This model is suitable for a variety of natural language processing tasks, particularly those benefiting from a Llama 3.1 foundation and efficient fine-tuning. Its 8 billion parameters make it a capable choice for applications requiring robust language understanding and generation.