I have added the jinja from Llama 3.2 3B, added all template tokens to the vocabulary, changed Ministral's built in [THINK] and [/THINK] tags to traditional <think> and </think> tags, padded to a multiple of 128 and resized the embeddings.
This is a base pretrain, ready for instruct training.
** Special Note: Due to the custom vocabulary, the tokenizer will not be recognized by llama.cpp, you will have to add its checksum to convert_hf_to_gguf.py before converting any derivatives to gguf.
