quyetdev/llama3.1_8B_fine_tuned_16bit
TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Jul 9, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The quyetdev/llama3.1_8B_fine_tuned_16bit is an 8 billion parameter Llama 3.1 instruction-tuned model, developed by quyetdev. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language tasks, leveraging its Llama 3.1 architecture and 8192 token context length.
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Model Overview
The quyetdev/llama3.1_8B_fine_tuned_16bit is an 8 billion parameter language model based on the Llama 3.1 architecture, developed by quyetdev. This model has been fine-tuned from unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit using a specialized training process.
Key Characteristics
- Architecture: Llama 3.1, an advanced open-source large language model family.
- Parameter Count: 8 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: Fine-tuned with Unsloth and Huggingface's TRL library, which significantly accelerated the training process (2x faster).
- Context Length: Supports an 8192 token context window, suitable for handling moderately long inputs and generating coherent responses.
Intended Use Cases
This fine-tuned Llama 3.1 model is suitable for a variety of natural language processing tasks, including:
- Instruction following and conversational AI.
- Text generation, summarization, and question answering.
- Applications requiring a capable 8B parameter model with efficient training origins.