sdhossain24/Meta-Llama-3-8B-SDD
The sdhossain24/Meta-Llama-3-8B-SDD model is a fine-tuned 8 billion parameter Llama 3-based causal language model, developed by sdhossain24. It was trained using SFT with the TRL framework and features an 8192-token context length. This model is optimized for general text generation tasks, building upon the robust capabilities of its Meta-Llama-3-8B base.
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Model Overview
The sdhossain24/Meta-Llama-3-8B-SDD is an 8 billion parameter language model, fine-tuned from the meta-llama/Meta-Llama-3-8B base model. It leverages the powerful Llama 3 architecture and has been specifically trained using Supervised Fine-Tuning (SFT) with the TRL library.
Key Capabilities
- General Text Generation: Excels at generating coherent and contextually relevant text based on user prompts.
- Instruction Following: Benefits from fine-tuning to better understand and execute instructions.
- 8K Context Window: Supports an 8192-token context length, allowing for processing and generating longer sequences of text.
Training Details
The model underwent a Supervised Fine-Tuning (SFT) process. The training utilized specific versions of popular machine learning frameworks:
- TRL: 0.22.1
- Transformers: 4.57.6
- Pytorch: 2.10.0+cu128
- Datasets: 4.8.4
- Tokenizers: 0.22.2
Use Cases
This model is suitable for a variety of applications requiring robust text generation, such as:
- Chatbots and Conversational AI: Generating human-like responses in interactive systems.
- Content Creation: Assisting with drafting articles, summaries, or creative writing.
- Question Answering: Providing informative answers to user queries.
Developers can quickly get started using the transformers library, as demonstrated in the quick start example provided in the original model card.