lhordking/Shadow-coder
Shadow-coder by lhordking is a 3.1 billion parameter language model with a 32768-token context length. This model is a general-purpose language model, though specific training details and primary differentiators are not provided in its current documentation. It is intended for various natural language processing tasks where a moderately sized model with a large context window is beneficial. Further information is needed to determine its specialized capabilities or optimal use cases.
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Model Overview
This model, lhordking/Shadow-coder, is a 3.1 billion parameter language model designed with a substantial 32768-token context length. While the model card indicates it is a Hugging Face transformers model, specific details regarding its architecture, training data, and development by lhordking are currently marked as "More Information Needed" in its official documentation.
Key Characteristics
- Parameter Count: 3.1 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Features a large 32768-token context window, enabling it to process and generate longer sequences of text.
Current Status
As per the provided model card, detailed information on its specific training objectives, performance benchmarks, and intended use cases is not yet available. Users should be aware that the model's full capabilities and potential limitations are still to be documented. Recommendations for its use are pending further information regarding its biases, risks, and technical specifications.