AlexHung29629/3.2_magistral_ties_merging is a 24 billion parameter language model. This model is a merged model, indicating it combines characteristics from multiple base models. Further details on its specific architecture, training, and primary differentiators are not provided in the available documentation, suggesting it may be a foundational or experimental merge.
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Overview
This model, named 3.2_magistral_ties_merging, is a 24 billion parameter language model. It is identified as a merged model, which typically means it integrates the strengths or characteristics of several underlying models to achieve a new performance profile. The model card indicates it was pushed to the Hugging Face Hub using the transformers library.
Key Characteristics
- Parameter Count: 24 billion parameters.
- Context Length: Supports a context length of 32768 tokens.
- Model Type: A merged model, suggesting a combination of different model architectures or weights.
Limitations and Further Information
The provided model card explicitly states that significant details regarding its development, funding, specific model type, language(s), license, finetuning origins, training data, training procedure, evaluation metrics, and results are currently "More Information Needed." This implies that comprehensive technical specifications, performance benchmarks, and intended use cases are not yet publicly detailed. Users should be aware of these informational gaps when considering this model for specific applications.
How to Get Started
While specific code examples are marked as "More Information Needed," the model is available on the Hugging Face Hub, implying it can be loaded and used with the standard transformers library methods once more details become available.