bryysteve/llama3-finetuned-rag-16bit-v1

TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Jun 24, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The bryysteve/llama3-finetuned-rag-16bit-v1 is an 8 billion parameter Llama 3.1 model, developed by bryysteve, specifically fine-tuned for Retrieval Augmented Generation (RAG) tasks. This model was trained using Unsloth and Hugging Face's TRL library, enabling 2x faster training. With an 8192-token context length, it is optimized for efficient and accurate information retrieval and generation.

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Model Overview

The bryysteve/llama3-finetuned-rag-16bit-v1 is an 8 billion parameter language model, developed by bryysteve, and fine-tuned from the unsloth/llama-3.1-8b-unsloth-bnb-4bit base model. It is designed for Retrieval Augmented Generation (RAG) applications, leveraging its fine-tuned capabilities to enhance information retrieval and response generation.

Key Characteristics

  • Base Model: Llama 3.1 (8B parameters).
  • Training Efficiency: Fine-tuned using Unsloth and Hugging Face's TRL library, resulting in a 2x speedup during the training process.
  • Context Length: Supports an 8192-token context window, suitable for processing longer documents or conversational histories in RAG workflows.
  • License: Distributed under the Apache-2.0 license.

Use Cases

This model is particularly well-suited for applications requiring:

  • Enhanced RAG Systems: Improving the accuracy and relevance of generated responses by integrating retrieved information.
  • Information Extraction: Efficiently extracting specific data points from large text corpora.
  • Question Answering: Providing precise answers based on a given context or retrieved documents.

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