Hyeongwon/P2-split3_prob_Llama-3.2-3B-Base_0524-1
Hyeongwon/P2-split3_prob_Llama-3.2-3B-Base_0524-1 is a 3.2 billion parameter language model fine-tuned from the meta-llama/Llama-3.2-3B architecture. This model was trained using the TRL library, focusing on specific probabilistic tasks. It is designed for text generation applications, particularly those benefiting from its fine-tuned capabilities.
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Model Overview
Hyeongwon/P2-split3_prob_Llama-3.2-3B-Base_0524-1 is a 3.2 billion parameter language model derived from the meta-llama/Llama-3.2-3B base model. It has undergone supervised fine-tuning (SFT) using the TRL (Transformer Reinforcement Learning) library, specifically version 0.25.1.
Key Characteristics
- Base Model: Fine-tuned from
meta-llama/Llama-3.2-3B. - Training Method: Utilizes Supervised Fine-Tuning (SFT).
- Frameworks: Trained with TRL 0.25.1, Transformers 4.57.3, Pytorch 2.9.1, Datasets 3.6.0, and Tokenizers 0.22.2.
- Context Length: Supports a context length of 32768 tokens.
Intended Use Cases
This model is suitable for text generation tasks, particularly those where its fine-tuned characteristics are beneficial. Developers can integrate it into their applications using the transformers library, as demonstrated in the quick start example for question answering and text generation.