wgcyeo/ci-feedback_both_ema_Llama-3.1-8B-Instruct_jsd_b0p8_ema0p999_ep30
The wgcyeo/ci-feedback_both_ema_Llama-3.1-8B-Instruct model is an 8 billion parameter instruction-tuned causal language model based on the Llama-3.1 architecture, featuring a 32768 token context length. This model is shared by wgcyeo and is a fine-tuned variant of the Llama-3.1-8B-Instruct base model. Its specific differentiators and primary use cases are not detailed in the provided information, suggesting it is a general-purpose instruction-following model.
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Overview
This model, wgcyeo/ci-feedback_both_ema_Llama-3.1-8B-Instruct_jsd_b0p8_ema0p999_ep30, is an 8 billion parameter instruction-tuned language model built upon the Llama-3.1 architecture. It supports a substantial context length of 32768 tokens, making it suitable for processing longer inputs and generating coherent, extended responses. The model is a fine-tuned version of the Llama-3.1-8B-Instruct base model, indicating an optimization for instruction-following tasks.
Key Characteristics
- Model Type: Instruction-tuned causal language model.
- Base Architecture: Llama-3.1.
- Parameter Count: 8 billion parameters.
- Context Length: 32768 tokens.
Limitations and Recommendations
The provided model card indicates that specific details regarding its development, funding, language support, license, training data, and evaluation results are currently marked as "More Information Needed." Users should be aware that without this information, the model's specific biases, risks, and limitations are not fully documented. It is recommended that users exercise caution and conduct their own evaluations to understand its suitability for particular applications, especially given the lack of detailed performance metrics or intended use cases.