jshwang370/fintech_gemma_2b_prac2
The jshwang370/fintech_gemma_2b_prac2 is a 2.5 billion parameter language model with an 8192 token context length. This model is a fine-tuned variant of the Gemma architecture, developed by jshwang370. Its primary differentiator and intended use case are currently unspecified in the provided documentation, suggesting it may be a foundational model or a work-in-progress for a specific domain.
Loading preview...
Model Overview
The jshwang370/fintech_gemma_2b_prac2 is a 2.5 billion parameter language model, featuring an 8192 token context length. This model is based on the Gemma architecture, developed by jshwang370. The provided model card indicates it is a Hugging Face Transformers model, but specific details regarding its development, funding, or fine-tuning origins are marked as "More Information Needed."
Key Characteristics
- Model Type: Gemma-based architecture.
- Parameter Count: 2.5 billion parameters.
- Context Length: 8192 tokens.
Intended Use and Limitations
The model card currently lacks specific information on direct use cases, downstream applications, or out-of-scope uses. Similarly, details on bias, risks, and limitations are marked as "More Information Needed," with a general recommendation for users to be aware of potential issues. Training data, procedures, and evaluation results are also not yet specified.
Getting Started
While specific usage instructions are pending, the model is intended to be used with the Hugging Face transformers library. Users are advised to consult future updates for detailed guidance on implementation and application.