mahiatlinux/MasherAI-v6.1-7B-checkpoint3-code3
The mahiatlinux/MasherAI-v6.1-7B-checkpoint3-code3 is a 7 billion parameter Mistral-based language model, fine-tuned from mahiatlinux/MasherAI-v6.1-7B-checkpoint3-code2. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. With an 8192-token context length, it is optimized for tasks benefiting from efficient fine-tuning and a Mistral architecture.
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Model Overview
mahiatlinux/MasherAI-v6.1-7B-checkpoint3-code3 is a 7 billion parameter language model developed by mahiatlinux. It is a Mistral-based model, specifically fine-tuned from mahiatlinux/MasherAI-v6.1-7B-checkpoint3-code2. A key characteristic of this model's development is its training methodology, which leveraged Unsloth and Huggingface's TRL library to achieve a reported 2x faster training speed.
Key Capabilities
- Efficient Training: Benefits from Unsloth's optimizations for faster fine-tuning.
- Mistral Architecture: Inherits the robust capabilities of the Mistral model family.
- Context Length: Supports an 8192-token context window, suitable for tasks requiring moderate input lengths.
Good For
- Developers looking for a Mistral-based model that has undergone efficient fine-tuning.
- Applications where faster training iteration cycles are beneficial.
- Tasks that align with the general capabilities of 7B parameter Mistral models, potentially with a focus on code-related applications given its checkpoint name.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.