Captain Eris_ Violet V0.420 12 B G G U F

Introduction

The Captain-Eris_Violet-V0.420-12B-GGUF model is a quantized version of the Nitral-AI/Captain-Eris_Violet-V0.420-12B model. It is designed for efficient performance using the GGUF format and was created using llama.cpp. This model supports English language tasks and merges capabilities from two original models: Epiculous/Violet_Twilight-v0.2 and Nitral-AI/Captain_BMO-12B.

Architecture

The model utilizes a merge of two foundational models:

• Epiculous/Violet_Twilight-v0.2
• Nitral-AI/Captain_BMO-12B

The merging process employed a spherical linear interpolation (slerp) method across specified layer ranges with a specific YAML configuration guiding the parameter adjustments.

Training

The model was trained by merging the first 40 layers of each original model using the slerp merge method. The parameters were finely tuned using specified filters for self_attn and mlp modules, with a final parameter value set at 0.420. The model uses bfloat16 data type for efficient computation.

Guide: Running Locally

1. Setup Environment: Ensure Python and the necessary libraries, such as transformers and llama.cpp, are installed.
2. Download Model: Obtain the model files from Hugging Face by visiting the model page.
3. Run Inference: Load the model into your application using the Hugging Face transformers library or a compatible inference tool.
4. Hardware Recommendations: For optimal performance, consider using cloud GPUs such as those offered by AWS, Google Cloud, or Azure. These resources can handle large model computations effectively.

License

The model is distributed under an "other" license, which may include specific usage restrictions not covered by standard open-source licenses. Users should verify compatibility with their intended use case.