Alphacode-AI/Alphallama3-8B_v2
Alphacode-AI/Alphallama3-8B_v2 is an 8 billion parameter causal language model developed by Alphacode-AI, fine-tuned from Meta-Llama-3-8B. This model leverages a custom in-house dataset to enhance its capabilities, offering an 8192-token context window. It is optimized for tasks benefiting from specialized data fine-tuning, building upon the robust Llama 3 architecture.
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Alphacode-AI/Alphallama3-8B_v2 Overview
Alphacode-AI/Alphallama3-8B_v2 is an 8 billion parameter language model developed by Alphacode-AI. It is a fine-tuned version of the Meta-Llama-3-8B base model, distinguishing itself through specialized training on Alphacode-AI's proprietary in-house custom dataset. This targeted fine-tuning aims to adapt the model for specific applications or improved performance on particular data distributions.
Key Capabilities
- Foundation Model: Built upon the robust and widely recognized Meta-Llama-3-8B architecture.
- Custom Data Fine-tuning: Enhanced using an exclusive in-house dataset, suggesting improved performance or specialization in areas covered by this data.
- Context Window: Supports an 8192-token context length, suitable for processing moderately long inputs and generating coherent responses.
Training Details
The model was trained using an A100x8 GPU configuration, leveraging DeepSpeed, HuggingFace TRL Trainer, and HuggingFace Accelerate for efficient and scalable training. This setup indicates a professional and optimized training pipeline.
Good For
- Applications requiring a Llama 3-based model with enhanced performance on specific, custom data domains.
- Developers looking for an 8B parameter model with a solid foundation and specialized fine-tuning.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.