Feature/add axk1

[kmswin1]

Add A.X K1 model architecture
What does this PR do?
This PR adds support for A.X K1, a large-scale Mixture-of-Experts (MoE) language model developed by SK Telecom. A.X K1 contains 519B total parameters with 33B active parameters per token, enabling strong reasoning performance with practical inference efficiency.

Paper: A.X K1 Technical Report (arXiv:2601.09200)
Model: skt/A.X-K1
License: Apache 2.0

Architecture overview
A.X K1 is a decoder-only Transformer with the following key design choices:

Sparse MoE: 61 layers (1 dense + 60 MoE), with 192 routed experts + 1 shared expert per MoE layer. 8 experts + 1 shared expert are activated per token.
Multi-Latent Attention (MLA): Compressed KV representations for efficient long-context inference.
Post-MLP RMSNorm: An additional RMSNorm applied after the MLP/MoE block in each layer, improving training stability in large-scale sparse settings.
Multi-Token Prediction (MTP): An auxiliary training objective that also enables speculative decoding at inference time.
Hybrid Reasoning (Think / Non-Think): Supports user-controllable reasoning depth within a single unified model.
Context length: 131,072 tokens
Vocab size: 163,840 (BBPE-based tokenizer optimized for EN, KO, ZH, JA, ES and code)

This PR includes

Model implementation (AXK1ForCausalLM, AXK1Model, AXK1Config)
Tokenizer integration (BBPE-based, 163,840 vocab)
Documentation and model card
Tests

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Who can review?
@ArthurZucker @Cyrilvallez — text model architecture addition