hZzy/mistral-7b-sft-7b-submission-win
hZzy/mistral-7b-sft-7b-submission-win is a 7 billion parameter language model fine-tuned from Mistral-7B-Instruct-v0.3. This model was trained using Supervised Fine-Tuning (SFT) with the TRL library, focusing on instruction-following tasks. It is designed for general text generation based on user prompts, leveraging the base model's strong performance.
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Model Overview
hZzy/mistral-7b-sft-7b-submission-win is a 7 billion parameter instruction-tuned language model. It is a fine-tuned variant of the mistralai/Mistral-7B-Instruct-v0.3 base model, developed by hZzy. The fine-tuning process utilized Supervised Fine-Tuning (SFT) techniques implemented with the TRL library.
Key Capabilities
- Instruction Following: The model is specifically trained to understand and respond to user instructions, making it suitable for conversational AI and prompt-based generation tasks.
- Text Generation: It can generate coherent and contextually relevant text based on a given prompt, leveraging the capabilities inherited from its Mistral-7B-Instruct-v0.3 foundation.
Training Details
The model was trained using the SFT method, with the training process monitored and visualized via Weights & Biases. Key framework versions used include TRL 0.20.0, Transformers 4.54.1, Pytorch 2.7.0+cu128, Datasets 4.0.0, and Tokenizers 0.21.4.
Intended Use
This model is well-suited for applications requiring a 7B parameter model that can effectively follow instructions and generate human-like text. It can be used for various natural language processing tasks where a fine-tuned instruction-following model is beneficial.