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Supposedly a simpler addition, a key difference to earlier models seems to be that it interleaves layers with RoPE attention and layers with no positional encoding, which allows the model to attend to tokens at an arbitrary distance. This may be beneficial with system prompts I guess - I have no actual experience with this model, and cannot provide you with further details than the links here, please contact the authors.
Model description
E.g., https://huggingface.co/CohereForAI/c4ai-command-r7b-12-2024
Supposedly a simpler addition, a key difference to earlier models seems to be that it interleaves layers with RoPE attention and layers with no positional encoding, which allows the model to attend to tokens at an arbitrary distance. This may be beneficial with system prompts I guess - I have no actual experience with this model, and cannot provide you with further details than the links here, please contact the authors.
Open source status
Provide useful links for the implementation
Implementation in
transformers
: https://github.com/huggingface/transformers/blob/main/src/transformers/models/cohere2/modeling_cohere2.pyPretrained model: https://huggingface.co/CohereForAI/c4ai-command-r7b-12-2024
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