dhanesh-hf/Jarvis-Titan-V10-SFT-Merged
Jarvis-Titan-V10-SFT-Merged is a 7.6 billion parameter language model developed by dhanesh-hf, featuring a 32768 token context length. This model is a fine-tuned variant, though specific architectural details and training data are not provided. Its primary application areas and unique differentiators are not explicitly detailed in the available information.
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Model Overview
This model, dhanesh-hf/Jarvis-Titan-V10-SFT-Merged, is a 7.6 billion parameter language model with a substantial context length of 32768 tokens. It is presented as a fine-tuned (SFT) model, indicating it has undergone further training on specific datasets to enhance its performance for particular tasks. However, the available model card does not provide detailed information regarding its specific architecture, the datasets used for its training or fine-tuning, or its intended primary use cases.
Key Characteristics
- Parameter Count: 7.6 billion parameters.
- Context Length: Supports a context window of 32768 tokens.
- Fine-tuned (SFT): Implies specialized training beyond a base model.
Limitations and Further Information
The model card indicates that significant details are "More Information Needed" across various sections, including its developers, funding, model type, language(s), license, and the base model it was fine-tuned from. Consequently, specific capabilities, direct use cases, downstream applications, and potential biases or risks are not detailed. Users are advised that further information is required to understand its full scope and appropriate applications.