sampluralis/llama-sft-sgd
The sampluralis/llama-sft-sgd model is a fine-tuned language model based on gshasiri/SmolLM3-Mid, developed by sampluralis. It was trained using Supervised Fine-Tuning (SFT) with the TRL framework. This model is designed for general text generation tasks, demonstrating capabilities in conversational responses.
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Model Overview
The sampluralis/llama-sft-sgd model is a fine-tuned variant of the gshasiri/SmolLM3-Mid base model. It was developed by sampluralis and specifically trained using Supervised Fine-Tuning (SFT) through the TRL library.
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on provided prompts.
- Conversational AI: Demonstrated ability to respond to open-ended questions, making it suitable for interactive applications.
- Fine-tuned Performance: Leverages SFT to adapt the base model for improved performance on specific tasks.
Training Details
The model's training procedure utilized the TRL framework (version 0.28.0) for Supervised Fine-Tuning. Other framework versions involved include Transformers 4.57.6, Pytorch 2.6.0+cu126, Datasets 4.6.1, and Tokenizers 0.22.2. Training progress and metrics can be visualized via Weights & Biases.
Good For
- General Text Generation: Ideal for tasks requiring creative or informative text output.
- Question Answering: Can be used to generate responses to direct or open-ended questions.
- Prototyping: Suitable for developers looking for a fine-tuned model for various NLP applications.