llama.cpp

Commit Graph

Author	SHA1	Message	Date
Xuan-Son Nguyen	59db9a357d	llama: dynamic head_dim and n_rot for SWA (#20301 ) * llama: dynamic head_dim and n_rot for SWA * also add gguf_writer wrappers * fix build * build_rope_shift arg reorder	2026-03-09 22:22:39 +01:00
3 a l i	2bf318fd2f	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>	2026-02-19 13:30:17 +01:00

Author

SHA1

Message

Date

Xuan-Son Nguyen

59db9a357d

llama: dynamic head_dim and n_rot for SWA (#20301 )

* llama: dynamic head_dim and n_rot for SWA

* also add gguf_writer wrappers

* fix build

* build_rope_shift arg reorder

2026-03-09 22:22:39 +01:00

3 a l i

2bf318fd2f

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>

2026-02-19 13:30:17 +01:00

2 Commits