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jukofyork/Kimi-K2-Instruct-DRAFT-0.6B-v3.0-GGUF
Kimi-K2-Instruct-DRAFT-0.6B-v3.0-GGUF is a machine learning model from jukofyork. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
A 0.6B parameter draft (speculative decoding) model for use with Kimi-K2-Instruct.
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From the Hugging Face model README
A 0.6B parameter draft (speculative decoding) model for use with Kimi-K2-Instruct.
See Kimi-K2-Instruct-DRAFT-0.6B-v3.0 for the models in transformers format, and a detailed explanation of how the model was created.
I've included the Q4_0 quants for 3 different context lengths:
Qwen2.5-0.5B doesn't allow for any of the other 4-bit quants to be made (and experimentation has shown using more or less than 4-bits for speculative decoding is a waste of time anwyay).llama.cpp using "static-YaRN" the scaling factor remains constant regardless of input length! Only use the longer context versions when processing long contexts is required...TikToken / SentencePiece tokenizer mismatch requires a small hack to convert_hf_to_gguf.py (see main model page for details).