Possible solution to allow K-quants on models with n_vocab!=32000 (#2148)

Possible solution to allow K-quants on models with n_vocab!=32000 (#2148)

* This allows LLAMA models that were previously incompatible with K quants to function mostly as normal. This happens when a model has a vocab != 32000, e.g 32001 which means it's not divisible by 256 or 64. Since the problematic dimensions only apply for `tok_embeddings.weight` and `output.weight` (dimentions 4096 x n_vocab), we can simply quantize these layers to Q8_0 whereas the majority of the hidden layers are still K-quanted since they have compatible dimensions.

* Fix indentation

Co-authored-by: Georgi Gerganov <redacted>
* As an alternative, to avoid failing on Metal due to lack of Q8_0 support, instead quantize tok_embeddings.weight to Q4_0 and retain output.weight as F16. This results in a net gain of about 55mb for a 7B model compared to previous approach, but should minimize adverse impact to model quality.

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Co-authored-by: Georgi Gerganov <redacted>