areef44/llama-3.1-8b-alpaca-id-dicoding
TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 16, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The areef44/llama-3.1-8b-alpaca-id-dicoding is an 8 billion parameter Llama 3.1 model, developed by areef44, and fine-tuned from unsloth/llama-3.1-8b-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. It is designed for general language tasks, leveraging the Llama 3.1 architecture.
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Model Overview
The areef44/llama-3.1-8b-alpaca-id-dicoding is an 8 billion parameter Llama 3.1-based language model, developed by areef44. It has been fine-tuned from the unsloth/llama-3.1-8b-unsloth-bnb-4bit base model, leveraging the Unsloth library for accelerated training.
Key Characteristics
- Base Architecture: Llama 3.1, providing a robust foundation for various NLP tasks.
- Parameter Count: 8 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process.
- Context Length: Supports a context length of 32768 tokens, allowing for processing longer inputs and generating more coherent responses.
Potential Use Cases
- General Text Generation: Suitable for a wide range of text generation tasks, including creative writing, summarization, and content creation.
- Instruction Following: As an Alpaca-ID fine-tuned model, it is likely optimized for following instructions and responding to prompts effectively.
- Research and Development: Can serve as a base for further experimentation and fine-tuning on specific downstream tasks, benefiting from its efficient training methodology.