quyetdev/llama31_8B_fine_tuned_16bit_v2

TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Jul 12, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The quyetdev/llama31_8B_fine_tuned_16bit_v2 is an 8 billion parameter Llama 3.1 instruction-tuned model, developed by quyetdev. This model was fine-tuned using the Unsloth library for accelerated training. It is optimized for general instruction-following tasks, leveraging its Llama 3.1 architecture and 8192 token context length.

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Model Overview

The quyetdev/llama31_8B_fine_tuned_16bit_v2 is an 8 billion parameter language model based on the Llama 3.1 architecture. It was developed by quyetdev and fine-tuned from the unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit base model.

Key Characteristics

  • Architecture: Llama 3.1
  • Parameters: 8 billion
  • Context Length: 8192 tokens
  • Training Efficiency: Fine-tuned using the Unsloth library and Hugging Face's TRL library, enabling 2x faster training.

Use Cases

This model is suitable for a variety of instruction-following tasks, benefiting from its Llama 3.1 foundation and efficient fine-tuning. Its 8B parameter count makes it a capable option for applications requiring a balance of performance and computational efficiency.