mikhail/llama.cpp-mtp-turboquant
1
0
Fork 0
Code Issues Pull Requests Actions 32 Packages Projects Releases Wiki Activity

mtmd, llama : Update HunyuanVL vision-language model support (#22037)

Browse Source 
* mtmd, llama : add HunyuanVL vision-language model support

- add LLM_ARCH_HUNYUAN_VL with M-RoPE (XD-RoPE) support
- add PROJECTOR_TYPE_HUNYUANVL with PatchMerger vision encoder
- add HunyuanVL-specific M-RoPE position encoding for image tokens
- add GGUF conversion for HunyuanVL vision and text models
- add smoke test in tools/mtmd/tests.sh

* fix: fix HunyuanVL XD-RoPE h/w section order

* fix: Remove redundant code

* convert : fix HunyuanOCR / HunyuanVL conversion
 - Tested locally: both HunyuanOCR and HunyuanVL-4B convert to GGUF
 - successfully and produce correct inference output on Metal (F16 / Q8_0).

* clip : fix -Werror=misleading-indentation in bilinear resize

* fix CI: convert_hf_to_gguf type check error
 - convert_hf_to_gguf.py: give HunyuanVLTextModel.__init__ an explicit `dir_model: Path` parameter so ty can infer the type for load_hparams instead of reporting `Unknown | None`.

---------

Co-authored-by: wendadawen <wendadawen@tencent.com>
This commit is contained in:
manayang
2026-04-22 17:58:43 +08:00
committed by GitHub
parent 750579ff14
commit 7bfe60fdf9
13 changed files with 336 additions and 27 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/models/hunyuan-dense.cpp
+30 -11
View File
@@ -6,6 +6,11 @@ llm_build_hunyuan_dense::llm_build_hunyuan_dense(const llama_model & model, cons
GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());
GGML_ASSERT(n_embd_head == n_rot);
const bool use_mrope = hparams.use_mrope();
int sections[4];
std::copy(std::begin(hparams.rope_sections), std::begin(hparams.rope_sections) + 4, sections);
ggml_tensor * cur;
ggml_tensor * inpL;
@@ -37,22 +42,36 @@ llm_build_hunyuan_dense::llm_build_hunyuan_dense(const llama_model & model, cons
auto [Qcur, Kcur, Vcur] = build_qkv(model.layers[il], cur,
n_embd_head, n_head, n_head_kv, il);
Qcur = ggml_rope_ext(
ctx0, Qcur, inp_pos, rope_factors,
n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
ext_factor, attn_factor, beta_fast, beta_slow
);
if (use_mrope) {
Qcur = ggml_rope_multi(
ctx0, Qcur, inp_pos, rope_factors,
n_rot, sections, rope_type, n_ctx_orig, freq_base, freq_scale,
ext_factor, attn_factor, beta_fast, beta_slow
);
Kcur = ggml_rope_multi(
ctx0, Kcur, inp_pos, rope_factors,
n_rot, sections, rope_type, n_ctx_orig, freq_base, freq_scale,
ext_factor, attn_factor, beta_fast, beta_slow
);
} else {
Qcur = ggml_rope_ext(
ctx0, Qcur, inp_pos, rope_factors,
n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
ext_factor, attn_factor, beta_fast, beta_slow
);
Kcur = ggml_rope_ext(
ctx0, Kcur, inp_pos, rope_factors,
n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
ext_factor, attn_factor, beta_fast, beta_slow
);
}
cb(Qcur, "Qcur", il);
cb(Kcur, "Kcur", il);
cb(Vcur, "Vcur", il);
Kcur = ggml_rope_ext(
ctx0, Kcur, inp_pos, rope_factors,
n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
ext_factor, attn_factor, beta_fast, beta_slow
);
Kcur = build_norm(Kcur,
model.layers[il].attn_k_norm, nullptr,
LLM_NORM_RMS, il);