loveisgone/Affine-luanzenai2802-5Cwcb7ypuNwAmak9dGMNFwV5LkZHMNwRJ8VeyXezqZmkTK4B
Affine-luanzenai2802-5Cwcb7ypuNwAmak9dGMNFwV5LkZHMNwRJ8VeyXezqZmkTK4B is a 14 billion parameter causal language model developed by loveisgone. This model was trained using Supervised Fine-Tuning (SFT) and is designed for general text generation tasks. It leverages the TRL, Transformers, Pytorch, Datasets, and Tokenizers frameworks for its training procedure. Its primary application is generating human-like text based on given prompts.
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Overview
Affine-luanzenai2802-5Cwcb7ypuNwAmak9dGMNFwV5LkZHMNwRJ8VeyXezqZmkTK4B is a 14 billion parameter language model developed by loveisgone, specifically fine-tuned using Supervised Fine-Tuning (SFT). This model is built upon established frameworks including TRL (Transformers Reinforcement Learning), Transformers, Pytorch, Datasets, and Tokenizers, indicating a robust and standard training methodology.
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on user prompts.
- Instruction Following: Designed to respond to instructions, as demonstrated by its use in a
text-generationpipeline with a user role prompt.
Training Details
- The model underwent a Supervised Fine-Tuning (SFT) process, which typically involves training on a dataset of input-output pairs to teach specific behaviors or styles.
- Key framework versions used include TRL 0.29.0, Transformers 5.2.0, Pytorch 2.10.0, Datasets 4.6.1, and Tokenizers 0.22.2.
Good For
- General Purpose Text Generation: Suitable for various applications requiring human-like text output.
- Prototyping: Can be used by developers to quickly integrate text generation capabilities into their projects using the provided
transformerspipeline example.