LorenaYannnnn/sycophancy-Qwen3-0.6B-OURS_self-seed_2
LorenaYannnnn/sycophancy-Qwen3-0.6B-OURS_self-seed_2 is a 0.8 billion parameter language model with a 32768 token context length. This model is based on the Qwen architecture and is a self-seeded variant. Its specific differentiators and primary use cases are not detailed in the provided information.
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Model Overview
This model, LorenaYannnnn/sycophancy-Qwen3-0.6B-OURS_self-seed_2, is a 0.8 billion parameter language model built upon the Qwen architecture. It features a substantial context length of 32768 tokens, indicating its potential for processing and generating longer sequences of text. The model is described as a "self-seed" variant, suggesting a particular training methodology or initialization, though further details are not provided in the available documentation.
Key Characteristics
- Architecture: Based on the Qwen model family.
- Parameter Count: 0.8 billion parameters.
- Context Length: Supports a context window of 32768 tokens.
- Training: Identified as a "self-seed" model, implying a specific training approach.
Intended Use
Due to the limited information in the model card, specific direct or downstream use cases are not explicitly defined. Users should exercise caution and conduct thorough evaluations to determine its suitability for particular applications, especially given the lack of details on its training data, evaluation metrics, and potential biases or limitations.