model : add JAIS-2 architecture support (#19488)

* model: add JAIS-2 architecture support

Add support for the JAIS-2 family of Arabic-English bilingual models
from Inception AI (https://huggingface.co/inceptionai/Jais-2-8B-Chat).

Architecture characteristics:
- LayerNorm (not RMSNorm) with biases
- ReLU² (ReLU squared) activation function
- Separate Q/K/V projections with biases
- Simple MLP without gate projection (up -> act -> down)
- RoPE positional embeddings
- GPT-2 BPE tokenizer

Supported model sizes:
- Jais-2-8B (32 layers, 26 heads, 3328 hidden)
- Jais-2-70B (68 layers, 56 heads, 7168 hidden)

Tested with quantizations: BF16, Q8_0, Q6_K, Q5_K_M, Q5_0, Q4_K_M, Q4_0, Q3_K_M, Q2_K

Note: JAIS-2 requires F32 precision accumulators for numerical stability
and uses standard attention (not flash attention) on CUDA backends.

* fix: run convert_hf_to_gguf_update.py for jais-2 tokenizer hash

* fix: use NEOX RoPE type for JAIS2

* fix: remove Q/K permutation (NEOX RoPE doesn't need it)

* fix: enable flash attention for JAIS2 (fixed by #19115)

* fix: add dedicated JAIS2 pre-tokenizer type and control vector support

- Add LLAMA_VOCAB_PRE_TYPE_JAIS2 with cascading whitespace regex
- Include original regex from tokenizer.json as comment
- Add build_cvec call for control vector support

* no longer necessary to override set_vocab

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

convert_hf_to_gguf.py

@@ -1163,6 +1163,9 @@ class TextModel(ModelBase):
         if chkhsh == "b53802fb28e26d645c3a310b34bfe07da813026ec7c7716883404d5e0f8b1901":
             # ref: https://huggingface.co/core42/jais-13b
             res = "jais"
+        if chkhsh == "bc5108ee1eb6a3d600cadd065f63190fbd0554dbc9e4bbd6a0d977970afc8d2a":
+            # ref: https://huggingface.co/inceptionai/Jais-2-8B-Chat
+            res = "jais-2"
         if chkhsh == "7b3e7548e4308f52a76e8229e4e6cc831195d0d1df43aed21ac6c93da05fec5f":
             # ref: https://huggingface.co/WisdomShell/CodeShell-7B
             res = "codeshell"
@@ -8633,6 +8636,17 @@ class T5EncoderModel(TextModel):
         yield from super().modify_tensors(data_torch, name, bid)
 
 
+@ModelBase.register("Jais2ForCausalLM")
+class Jais2Model(TextModel):
+    model_arch = gguf.MODEL_ARCH.JAIS2
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        hparams = self.hparams
+        head_dim = hparams.get("head_dim", hparams["hidden_size"] // hparams["num_attention_heads"])
+        self.gguf_writer.add_rope_dimension_count(head_dim)
+
+
 @ModelBase.register("JAISLMHeadModel")
 class JaisModel(TextModel):
     model_arch = gguf.MODEL_ARCH.JAIS