wvnvwn/Mistral-7B-Instruct-v0.3-spider-v1
wvnvwn/Mistral-7B-Instruct-v0.3-spider-v1 is a 7 billion parameter instruction-tuned language model, fine-tuned from mistralai/Mistral-7B-Instruct-v0.3. This model was trained using the TRL library and features a 4096-token context length. It is optimized for general instruction-following tasks, leveraging its Mistral architecture for efficient processing.
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Model Overview
wvnwvn/Mistral-7B-Instruct-v0.3-spider-v1 is a 7 billion parameter instruction-tuned language model, building upon the robust mistralai/Mistral-7B-Instruct-v0.3 base. This model has been fine-tuned using the TRL library, a framework for Transformer Reinforcement Learning, to enhance its instruction-following capabilities.
Key Capabilities
- Instruction Following: Designed to accurately interpret and execute user instructions, making it suitable for a variety of prompt-based tasks.
- Mistral Architecture: Benefits from the efficient and performant architecture of the Mistral-7B series.
- SFT Training: Utilizes Supervised Fine-Tuning (SFT) as its training procedure, as detailed in its Weights & Biases run.
Training Details
The model's training leveraged specific versions of key frameworks:
- TRL: 1.4.0
- Transformers: 4.57.1
- Pytorch: 2.11.0
- Datasets: 4.8.5
- Tokenizers: 0.22.2
This fine-tuned model is well-suited for applications requiring a capable and responsive instruction-tuned language model within a 7B parameter budget.