Deepnoid/deep-solar-v2.0.7
Deepnoid/deep-solar-v2.0.7 is a 10.7 billion parameter language model developed by Deepnoid. This model is built with Axolotl, indicating a focus on efficient training and fine-tuning. Its primary differentiator and use case are not explicitly detailed in the provided README, suggesting a general-purpose application or a base model for further specialization.
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Deepnoid/deep-solar-v2.0.7 Model Summary
This model, Deepnoid/deep-solar-v2.0.7, is a 10.7 billion parameter language model. Developed by Deepnoid, it was built using the Axolotl framework, which is known for facilitating efficient training and fine-tuning of large language models. The use of Axolotl suggests that this model may be optimized for adaptability and ease of further development or specialization.
Key Characteristics
- Parameter Count: 10.7 billion parameters, placing it in the medium-to-large scale LLM category.
- Context Length: Supports a context length of 4096 tokens.
- Development Framework: Built with Axolotl, indicating a focus on streamlined training and potential for custom fine-tuning.
Potential Use Cases
Given the available information, Deepnoid/deep-solar-v2.0.7 appears to be a general-purpose language model suitable for a range of applications. Its 10.7 billion parameters suggest capabilities for complex language understanding and generation tasks. The Axolotl foundation implies it could be particularly useful as a base model for developers looking to fine-tune for specific domains or tasks where efficient training and customization are priorities.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.