NathanRoll/Llama-3.2-1B-Instruct-0k-shuffle-x
NathanRoll/Llama-3.2-1B-Instruct-0k-shuffle-x is a 1 billion parameter instruction-tuned language model developed by NathanRoll. This model is based on the Llama-3.2 architecture and features a substantial 32,768 token context length. Its primary differentiator and intended use case are not specified in the provided information, indicating it may be a base model or a preliminary instruction-tuned variant.
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Model Overview
This model, NathanRoll/Llama-3.2-1B-Instruct-0k-shuffle-x, is a 1 billion parameter instruction-tuned language model. Developed by NathanRoll, it is built upon the Llama-3.2 architecture and supports a context length of 32,768 tokens. The model card indicates that this is a Hugging Face Transformers model, automatically pushed to the Hub.
Key Characteristics
- Model Family: Llama-3.2 architecture.
- Parameter Count: 1 billion parameters.
- Context Length: Supports a long context window of 32,768 tokens.
- Instruction-Tuned: Designed to follow instructions, though specific tuning details are not provided.
Intended Use and Limitations
The provided model card does not specify direct use cases, downstream applications, or out-of-scope uses. Similarly, detailed information regarding training data, evaluation metrics, or known biases and limitations is marked as "More Information Needed." Users should be aware that without further details, the specific strengths, weaknesses, and appropriate applications of this model are not clearly defined. It is recommended to exercise caution and conduct thorough testing for any specific use case.