Heralax/Mannerstral-base
Heralax/Mannerstral-base is a 7 billion parameter foundational language model, derived from Alpindale/Mistral-7B-v0.2-hf and trained with a 4096 token context length. This model serves as a pre-trained base, specifically designed for further fine-tuning, rather than direct inference. Its primary use case is to provide a robust starting point for developers building specialized language models.
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Heralax/Mannerstral-base: A Foundational Pre-trained Model
Heralax/Mannerstral-base is a 7 billion parameter language model built upon the Alpindale/Mistral-7B-v0.2-hf architecture. It was developed using Axolotl, a framework for fine-tuning large language models. This model is not intended for direct use in applications but rather as a robust, pre-trained base for subsequent fine-tuning tasks.
Key Characteristics
- Base Model: Derived from Alpindale/Mistral-7B-v0.2-hf, inheriting its core architectural strengths.
- Parameter Count: 7 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a sequence length of 4096 tokens, suitable for processing moderately long inputs.
- Training: Utilizes
hidden_pretraining_manners.jsonldataset, indicating a specialized pre-training focus.
Good For
- Further Fine-tuning: Ideal for developers who need a strong, pre-trained foundation to adapt to specific domains or tasks.
- Experimental Development: Provides a stable base for experimenting with different fine-tuning methodologies and datasets.
- Resource-Efficient Customization: Offers a powerful starting point without the need to train a model from scratch, making custom model development more accessible.