Alelcv27/llama3-1b-datamerged-dpo
TEXT GENERATIONPricing:Input $0.108 / Output $0.804Concurrent Unit Cost:1Model Size:1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Oct 28, 2025License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Warm
Alelcv27/llama3-1b-datamerged-dpo is a 1 billion parameter Llama 3 model developed by Alelcv27, fine-tuned from unsloth/llama-3.2-1b-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. It is designed for efficient performance in tasks suitable for a compact language model, leveraging its optimized training process.
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Model Overview
Alelcv27/llama3-1b-datamerged-dpo is a compact 1 billion parameter language model, fine-tuned by Alelcv27. It is based on the Llama 3 architecture, specifically fine-tuned from the unsloth/llama-3.2-1b-bnb-4bit model.
Key Characteristics
- Efficient Training: This model was trained significantly faster, achieving a 2x speedup, by utilizing the Unsloth library in conjunction with Huggingface's TRL library. This optimization allows for quicker iteration and development cycles.
- Compact Size: With 1 billion parameters, it is suitable for applications requiring a smaller footprint and faster inference times compared to larger models.
- License: The model is released under the Apache-2.0 license, promoting open and flexible use.
Potential Use Cases
This model is well-suited for:
- Edge device deployment: Its small size makes it ideal for running on devices with limited computational resources.
- Rapid prototyping: The efficient training process allows for quick experimentation and fine-tuning for specific tasks.
- Lightweight applications: Suitable for tasks where a full-scale large language model might be overkill, such as simple text generation, classification, or summarization.