[Misc] Support FP8 kv cache scales from compressed-tensors

[mgoin]

Adding the logic for loading models with quantized kv cache scales, generated using compressed-tensors framework.

• CompressedTensorsConfig now has an optional kv_cache_scheme argument. As of the next compressed-tensors release, the key contains the information about the properties of the quantized kv cache.
• Added an interface BaseKVCacheMethod that both Fp8KVCacheMethod and CompressedTensorsKVCacheMethod inherits from, to prepare the k_scale and v_scale attributes of the quantized Attention layer.

Currently, the loading of the kv cache scales happens inside the load_model method of the model (in this PR only LLaMa model), just like previous kv scales. However, it needs to happen before the parameter names get mapped to stacked params since we are looking for k_proj.output_scale and v_proj.output_scale. Thich is a bit ugly because we need to copy and paste the helper function into every model to make it read quantized kv cache.

Done in collaboration with @dbogunowicz

[github-actions]

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[comaniac]

Overall LGTM