123yaroslav/Qwen2.5-0.5B-Instruct-abliterated-ru
The 123yaroslav/Qwen2.5-0.5B-Instruct-abliterated-ru model is a 0.5 billion parameter instruction-tuned language model based on the Qwen2.5 architecture. This model is shared by 123yaroslav and features a context length of 32768 tokens. Specific details regarding its training, language focus, and primary differentiators are not provided in the available model card. Its small size suggests potential for efficient deployment in resource-constrained environments.
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Model Overview
This model, 123yaroslav/Qwen2.5-0.5B-Instruct-abliterated-ru, is a 0.5 billion parameter instruction-tuned model built upon the Qwen2.5 architecture. It is shared by 123yaroslav and supports a substantial context length of 32768 tokens, which is notable for its parameter count.
Key Characteristics
- Architecture: Qwen2.5-based instruction-tuned model.
- Parameter Count: 0.5 billion parameters, indicating a relatively small and efficient model size.
- Context Length: Features a 32768-token context window, allowing for processing of longer inputs.
Limitations and Further Information
The provided model card indicates that specific details regarding the model's development, language(s) supported, training data, evaluation results, and intended use cases are currently marked as "More Information Needed." Users should be aware that comprehensive information on its performance, biases, risks, and optimal applications is not yet available. Recommendations for use are pending further details from the developer.