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ngxsonnisparks
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llama : add Phi-4-mini support (supersede #12099) (#12108)
* Added Phi-4-mini-instruct support * Update regex per ngxson * Change the vocab base to Xenova/gpt-4o * fix conversion update script * no need to check longrope * minor style fix * fix python style --------- Co-authored-by: Nicholas Sparks <[email protected]>
1 parent 84d5f4b commit c43a3e7

7 files changed

+191
-8
lines changed

‎convert_hf_to_gguf.py

+8-3
Original file line numberDiff line numberDiff line change
@@ -699,6 +699,9 @@ def get_vocab_base_pre(self, tokenizer) -> str:
699699
if chkhsh == "b3f499bb4255f8ca19fccd664443283318f2fd2414d5e0b040fbdd0cc195d6c5":
700700
# ref: https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
701701
res = "deepseek-r1-qwen"
702+
if chkhsh == "ccc2ef013c104be7bae2965776d611e1d7a8a2a9c547dd93a682c9a9fc80352e":
703+
# ref: https://huggingface.co/Xenova/gpt-4o
704+
res = "gpt-4o"
702705

703706
if res is None:
704707
logger.warning("\n")
@@ -2512,7 +2515,8 @@ def set_gguf_parameters(self):
25122515
rms_eps = self.find_hparam(["rms_norm_eps"])
25132516
max_pos_embds = self.find_hparam(["n_positions", "max_position_embeddings"])
25142517
orig_max_pos_embds = self.find_hparam(["original_max_position_embeddings"])
2515-
rope_dims = n_embd // n_head
2518+
rot_pct = self.hparams.get("partial_rotary_factor", 1.0)
2519+
rope_dims = int(rot_pct * n_embd) // n_head
25162520

25172521
self.gguf_writer.add_context_length(max_pos_embds)
25182522
self.gguf_writer.add_rope_scaling_orig_ctx_len(orig_max_pos_embds)
@@ -2536,7 +2540,8 @@ def generate_extra_tensors(self) -> Iterable[tuple[str, Tensor]]:
25362540
n_head = self.find_hparam(["num_attention_heads", "n_head"])
25372541
max_pos_embds = self.find_hparam(["n_positions", "max_position_embeddings"])
25382542
orig_max_pos_embds = self.find_hparam(["original_max_position_embeddings"])
2539-
rope_dims = n_embd // n_head
2543+
rot_pct = self.hparams.get("partial_rotary_factor", 1.0)
2544+
rope_dims = int(rot_pct * n_embd) // n_head
25402545

25412546
# write rope scaling for long context (128k) model
25422547
rope_scaling = self.find_hparam(['rope_scaling'], True)
@@ -2565,7 +2570,7 @@ def generate_extra_tensors(self) -> Iterable[tuple[str, Tensor]]:
25652570
raise KeyError('Missing the required key rope_scaling.long_factor or rope_scaling_short_factor')
25662571

25672572
if len(long_factors) != len(short_factors) or len(long_factors) != rope_dims / 2:
2568-
raise ValueError(f'The length of rope long and short factors must be {rope_dims / 2}')
2573+
raise ValueError(f'The length of rope long and short factors must be {rope_dims / 2}. long_factors = {len(long_factors)}, short_factors = {len(short_factors)}.')
25692574

25702575
yield (self.format_tensor_name(gguf.MODEL_TENSOR.ROPE_FACTORS_LONG), torch.tensor(long_factors, dtype=torch.float32))
25712576
yield (self.format_tensor_name(gguf.MODEL_TENSOR.ROPE_FACTORS_SHORT), torch.tensor(short_factors, dtype=torch.float32))

‎convert_hf_to_gguf_update.py

+5
Original file line numberDiff line numberDiff line change
@@ -109,6 +109,7 @@ class TOKENIZER_TYPE(IntEnum):
109109
{"name": "megrez", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/Infinigence/Megrez-3B-Instruct"},
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{"name": "deepseek-v3", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/deepseek-ai/DeepSeek-V3"},
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{"name": "deepseek-r1-qwen", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B"},
112+
{"name": "gpt-4o", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/Xenova/gpt-4o", },
112113
]
113114

114115

@@ -131,6 +132,10 @@ def download_model(model):
131132

132133
files = ["config.json", "tokenizer.json", "tokenizer_config.json"]
133134

135+
if name == "gpt-4o":
136+
# Xenova/gpt-4o is tokenizer-only, it does not contain config.json
137+
files = ["tokenizer.json", "tokenizer_config.json"]
138+
134139
if tokt == TOKENIZER_TYPE.SPM:
135140
files.append("tokenizer.model")
136141

‎include/llama.h

+1
Original file line numberDiff line numberDiff line change
@@ -105,6 +105,7 @@ extern "C" {
105105
LLAMA_VOCAB_PRE_TYPE_CHAMELEON = 26,
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LLAMA_VOCAB_PRE_TYPE_MINERVA = 27,
107107
LLAMA_VOCAB_PRE_TYPE_DEEPSEEK3_LLM = 28,
108+
LLAMA_VOCAB_PRE_TYPE_GPT4O = 29,
108109
};
109110

110111
enum llama_rope_type {

‎models/ggml-vocab-gpt-4o.gguf.inp

+112
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@@ -0,0 +1,112 @@
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ied 4 ½ months
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__ggml_vocab_test__
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Führer
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Hello world
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Hello world
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Hello World
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Hello World
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Hello World!
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Hello, world!
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Hello, world!
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this is 🦙.cpp
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w048 7tuijk dsdfhu
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нещо на Български
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កាន់តែពិសេសអាចខលចេញ
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__ggml_vocab_test__
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🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
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__ggml_vocab_test__
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Hello
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Hello
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Hello
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Hello
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(
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=
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' era
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Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
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!!!!!!
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3
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Cửa Việt
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discards
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🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
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__ggml_vocab_test__

‎models/ggml-vocab-gpt-4o.gguf.out

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‎src/llama-model.cpp

+8-5
Original file line numberDiff line numberDiff line change
@@ -2202,13 +2202,16 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
22022202
} break;
22032203
case LLM_ARCH_PHI3:
22042204
{
2205-
const int64_t n_embd_head = n_embd / n_head;
2206-
22072205
tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), { n_embd, n_vocab }, 0);
22082206

22092207
// output
22102208
output_norm = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), { n_embd }, 0);
2211-
output = create_tensor(tn(LLM_TENSOR_OUTPUT, "weight"), { n_embd, n_vocab }, 0);
2209+
output = create_tensor(tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, TENSOR_NOT_REQUIRED);
2210+
2211+
// if output is NULL, init from the input tok embed
2212+
if (output == NULL) {
2213+
output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED);
2214+
}
22122215

22132216
for (int i = 0; i < n_layer; ++i) {
22142217
auto & layer = layers[i];
@@ -2223,8 +2226,8 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
22232226
layer.ffn_down = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), { n_ff, n_embd }, 0);
22242227
layer.ffn_up = create_tensor(tn(LLM_TENSOR_FFN_UP, "weight", i), { n_embd, 2 * n_ff }, 0);
22252228

2226-
layer.rope_long = create_tensor(tn(LLM_TENSOR_ROPE_FACTORS_LONG, "weight", i), { n_embd_head/2 }, TENSOR_NOT_REQUIRED | (i != 0 ? TENSOR_DUPLICATED : 0));
2227-
layer.rope_short = create_tensor(tn(LLM_TENSOR_ROPE_FACTORS_SHORT, "weight", i), { n_embd_head/2 }, TENSOR_NOT_REQUIRED | (i != 0 ? TENSOR_DUPLICATED : 0));
2229+
layer.rope_long = create_tensor(tn(LLM_TENSOR_ROPE_FACTORS_LONG, "weight", i), { n_rot/2 }, TENSOR_NOT_REQUIRED | (i != 0 ? TENSOR_DUPLICATED : 0));
2230+
layer.rope_short = create_tensor(tn(LLM_TENSOR_ROPE_FACTORS_SHORT, "weight", i), { n_rot/2 }, TENSOR_NOT_REQUIRED | (i != 0 ? TENSOR_DUPLICATED : 0));
22282231
}
22292232
} break;
22302233
case LLM_ARCH_PHIMOE:

‎src/llama-vocab.cpp

+11
Original file line numberDiff line numberDiff line change
@@ -392,6 +392,13 @@ struct llm_tokenizer_bpe : llm_tokenizer {
392392
"'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
393393
};
394394
break;
395+
case LLAMA_VOCAB_PRE_TYPE_GPT4O:
396+
regex_exprs = {
397+
// original regex from tokenizer.json
398+
// "[^\\r\\n\\p{L}\\p{N}]?[\\p{Lu}\\p{Lt}\\p{Lm}\\p{Lo}\\p{M}]*[\\p{Ll}\\p{Lm}\\p{Lo}\\p{M}]+(?i:'s|'t|'re|'ve|'m|'ll|'d)?|[^\\r\\n\\p{L}\\p{N}]?[\\p{Lu}\\p{Lt}\\p{Lm}\\p{Lo}\\p{M}]+[\\p{Ll}\\p{Lm}\\p{Lo}\\p{M}]*(?i:'s|'t|'re|'ve|'m|'ll|'d)?|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n/]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
399+
"[^\\r\\n\\p{L}\\p{N}]?((?=[\\p{L}])([^a-z]))*((?=[\\p{L}])([^A-Z]))+(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])?|[^\\r\\n\\p{L}\\p{N}]?((?=[\\p{L}])([^a-z]))+((?=[\\p{L}])([^A-Z]))*(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])?|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n/]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
400+
};
401+
break;
395402
default:
396403
// default regex for BPE tokenization pre-processing
397404
regex_exprs = {
@@ -1592,6 +1599,10 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
15921599
} else if (
15931600
tokenizer_pre == "megrez") {
15941601
pre_type = LLAMA_VOCAB_PRE_TYPE_QWEN2;
1602+
} else if (
1603+
tokenizer_pre == "gpt-4o") {
1604+
pre_type = LLAMA_VOCAB_PRE_TYPE_GPT4O;
1605+
clean_spaces = false;
15951606
} else {
15961607
throw std::runtime_error(format("unknown pre-tokenizer type: '%s'", tokenizer_pre.c_str()));
15971608
}

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