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llama : add support for Chameleon (ggml-org#8543)
* convert chameleon hf to gguf * add chameleon tokenizer tests * fix lint * implement chameleon graph * add swin norm param * return qk norm weights and biases to original format * implement swin norm * suppress image token output * rem tabs * add comment to conversion * fix ci * check for k norm separately * adapt to new lora implementation * fix layer input for swin norm * move swin_norm in gguf writer * add comment regarding special token regex in chameleon pre-tokenizer * Update src/llama.cpp Co-authored-by: compilade <[email protected]> * fix punctuation regex in chameleon pre-tokenizer (@compilade) Co-authored-by: compilade <[email protected]> * fix lint * trigger ci --------- Co-authored-by: compilade <[email protected]>
1 parent b697557 commit 84597bf

10 files changed

+505
-2
lines changed

‎convert_hf_to_gguf.py

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@@ -640,6 +640,9 @@ def get_vocab_base_pre(self, tokenizer) -> str:
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if chkhsh == "fcace8b9cac38ce847670c970cd5892031a753a1ef381abd1d9af00f713da085":
641641
# ref: https://huggingface.co/microsoft/phi-2
642642
res = "phi-2"
643+
if chkhsh == "60824e3c0d9401f89943cbb2fff727f0e2d4c545ba4df2d6e4f09a6db0f5b450":
644+
# ref: https://huggingface.co/facebook/chameleon-7b
645+
res = "chameleon"
643646

644647
if res is None:
645648
logger.warning("\n")
@@ -4138,6 +4141,47 @@ def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iter
41384141
return super().modify_tensors(data_torch, name, bid)
41394142

41404143

4144+
@Model.register("ChameleonForCausalLM")
4145+
class ChameleonModel(Model):
4146+
model_arch = gguf.MODEL_ARCH.CHAMELEON
4147+
4148+
def set_gguf_parameters(self):
4149+
super().set_gguf_parameters()
4150+
self.gguf_writer.add_swin_norm(self.hparams.get("swin_norm", False))
4151+
4152+
def set_vocab(self):
4153+
self._set_vocab_gpt2()
4154+
4155+
def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
4156+
# ignore image tokenizer for now
4157+
# TODO: remove this once image support is implemented for Chameleon
4158+
if name.startswith("model.vqmodel"):
4159+
return []
4160+
4161+
n_head = self.hparams["num_attention_heads"]
4162+
n_kv_head = self.hparams.get("num_key_value_heads")
4163+
hidden_dim = self.hparams.get("hidden_size")
4164+
4165+
if name.endswith(("q_proj.weight", "q_proj.bias")):
4166+
data_torch = LlamaModel.permute(data_torch, n_head, n_head)
4167+
if name.endswith(("k_proj.weight", "k_proj.bias")):
4168+
data_torch = LlamaModel.permute(data_torch, n_head, n_kv_head)
4169+
if name.endswith(("q_norm.weight", "q_norm.bias")):
4170+
data_torch = ChameleonModel._reverse_hf_permute(data_torch, n_head, hidden_dim)
4171+
if name.endswith(("k_norm.weight", "k_norm.bias")):
4172+
data_torch = ChameleonModel._reverse_hf_permute(data_torch, n_kv_head, hidden_dim)
4173+
4174+
return [(self.map_tensor_name(name), data_torch)]
4175+
4176+
# see: https://github.com/huggingface/transformers/blob/72fb02c47dbbe1999ae105319f24631cad6e2e00/src/transformers/models/chameleon/convert_chameleon_weights_to_hf.py#L176-L203
4177+
@staticmethod
4178+
def _reverse_hf_permute(data_torch, n_heads, hidden_dim):
4179+
head_dim = hidden_dim // n_heads
4180+
data_torch = data_torch[0].view(2, head_dim // 2).t().reshape(1, -1)
4181+
data_torch = data_torch.repeat_interleave(n_heads, 0)
4182+
return data_torch
4183+
4184+
41414185
###### CONVERSION LOGIC ######
41424186

41434187

‎convert_hf_to_gguf_update.py

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@@ -99,6 +99,7 @@ class TOKENIZER_TYPE(IntEnum):
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{'name': "gpt3-finnish", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/TurkuNLP/gpt3-finnish-small", },
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{"name": "exaone", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct", },
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{"name": "phi-2", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/microsoft/phi-2", },
102+
{"name": "chameleon", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/facebook/chameleon-7b", },
102103
]
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104105

‎gguf-py/gguf/constants.py

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@@ -94,6 +94,7 @@ class LLM:
9494
DECODER_START_TOKEN_ID = "{arch}.decoder_start_token_id"
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ATTN_LOGIT_SOFTCAPPING = "{arch}.attn_logit_softcapping"
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FINAL_LOGIT_SOFTCAPPING = "{arch}.final_logit_softcapping"
97+
SWIN_NORM = "{arch}.swin_norm"
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RESCALE_EVERY_N_LAYERS = "{arch}.rescale_every_n_layers"
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TIME_MIX_EXTRA_DIM = "{arch}.time_mix_extra_dim"
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TIME_DECAY_EXTRA_DIM = "{arch}.time_decay_extra_dim"
@@ -236,6 +237,7 @@ class MODEL_ARCH(IntEnum):
236237
EXAONE = auto()
237238
GRANITE = auto()
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GRANITE_MOE = auto()
240+
CHAMELEON = auto()
239241

240242

241243
class MODEL_TENSOR(IntEnum):
@@ -394,6 +396,7 @@ class MODEL_TENSOR(IntEnum):
394396
MODEL_ARCH.EXAONE: "exaone",
395397
MODEL_ARCH.GRANITE: "granite",
396398
MODEL_ARCH.GRANITE_MOE: "granitemoe",
399+
MODEL_ARCH.CHAMELEON: "chameleon",
397400
}
398401

399402
TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
@@ -1260,6 +1263,22 @@ class MODEL_TENSOR(IntEnum):
12601263
MODEL_TENSOR.FFN_DOWN_EXP,
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MODEL_TENSOR.FFN_UP_EXP,
12621265
],
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MODEL_ARCH.CHAMELEON: [
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MODEL_TENSOR.TOKEN_EMBD,
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MODEL_TENSOR.OUTPUT_NORM,
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MODEL_TENSOR.OUTPUT,
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MODEL_TENSOR.ATTN_NORM,
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MODEL_TENSOR.ATTN_Q,
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MODEL_TENSOR.ATTN_Q_NORM,
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MODEL_TENSOR.ATTN_K,
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MODEL_TENSOR.ATTN_K_NORM,
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MODEL_TENSOR.ATTN_V,
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MODEL_TENSOR.ATTN_OUT,
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MODEL_TENSOR.FFN_NORM,
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MODEL_TENSOR.FFN_GATE,
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MODEL_TENSOR.FFN_DOWN,
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MODEL_TENSOR.FFN_UP,
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],
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# TODO
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}
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‎gguf-py/gguf/gguf_writer.py

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@@ -670,6 +670,9 @@ def add_expert_shared_count(self, count: int) -> None:
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def add_expert_weights_scale(self, value: float) -> None:
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self.add_float32(Keys.LLM.EXPERT_WEIGHTS_SCALE.format(arch=self.arch), value)
672672

673+
def add_swin_norm(self, value: bool) -> None:
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self.add_bool(Keys.LLM.SWIN_NORM.format(arch=self.arch), value)
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def add_rescale_every_n_layers(self, count: int) -> None:
674677
self.add_uint32(Keys.LLM.RESCALE_EVERY_N_LAYERS.format(arch=self.arch), count)
675678

‎gguf-py/gguf/tensor_mapping.py

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@@ -380,7 +380,7 @@ class TensorNameMap:
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MODEL_TENSOR.ATTN_Q_NORM: (
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"language_model.encoder.layers.{bid}.self_attention.q_layernorm",
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"model.layers.{bid}.self_attn.q_layernorm", # persimmon
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"model.layers.{bid}.self_attn.q_norm", # cohere olmoe
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"model.layers.{bid}.self_attn.q_norm", # cohere olmoe chameleon
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"transformer.blocks.{bid}.attn.q_ln", # sea-lion
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"encoder.layer.{bid}.attention.self.layer_norm_q", # jina-bert-v2
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"transformer.layers.{bid}.attn.q_norm", # openelm
@@ -389,7 +389,7 @@ class TensorNameMap:
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MODEL_TENSOR.ATTN_K_NORM: (
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"language_model.encoder.layers.{bid}.self_attention.k_layernorm",
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"model.layers.{bid}.self_attn.k_layernorm", # persimmon
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"model.layers.{bid}.self_attn.k_norm", # cohere olmoe
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"model.layers.{bid}.self_attn.k_norm", # cohere olmoe chameleon
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"transformer.blocks.{bid}.attn.k_ln", # sea-lion
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"encoder.layer.{bid}.attention.self.layer_norm_k", # jina-bert-v2
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"transformer.layers.{bid}.attn.k_norm", # openelm

‎include/llama.h

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@@ -102,6 +102,7 @@ extern "C" {
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LLAMA_VOCAB_PRE_TYPE_BLOOM = 23,
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LLAMA_VOCAB_PRE_TYPE_GPT3_FINNISH = 24,
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LLAMA_VOCAB_PRE_TYPE_EXAONE = 25,
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LLAMA_VOCAB_PRE_TYPE_CHAMELEON = 26,
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};
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enum llama_rope_type {

‎models/ggml-vocab-chameleon.gguf.inp

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ied 4 ½ months
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__ggml_vocab_test__
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Führer
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__ggml_vocab_test__
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__ggml_vocab_test__
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__ggml_vocab_test__
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__ggml_vocab_test__
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__ggml_vocab_test__
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Hello world
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__ggml_vocab_test__
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Hello world
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__ggml_vocab_test__
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Hello World
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__ggml_vocab_test__
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Hello World
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__ggml_vocab_test__
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Hello World!
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__ggml_vocab_test__
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Hello, world!
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__ggml_vocab_test__
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Hello, world!
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__ggml_vocab_test__
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this is 🦙.cpp
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__ggml_vocab_test__
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w048 7tuijk dsdfhu
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__ggml_vocab_test__
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нещо на Български
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__ggml_vocab_test__
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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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__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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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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33
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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-chameleon.gguf.out

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‎src/llama-vocab.cpp

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@@ -450,6 +450,20 @@ struct llm_tokenizer_bpe {
450450
"[^\\r\\n\\p{L}\\p{N}]?((?=[\\p{L}])([^a-z]))*((?=[\\p{L}])([^A-Z]))+|[^\\r\\n\\p{L}\\p{N}]?((?=[\\p{L}])([^a-z]))+((?=[\\p{L}])([^A-Z]))*|\\p{N}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n/]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
451451
};
452452
break;
453+
case LLAMA_VOCAB_PRE_TYPE_CHAMELEON:
454+
// Note: in theory, the special token (sentinel and image token) regex_exprs below
455+
// are unnecessary, as they are split in `tokenizer_st_partition` anyway.
456+
// However, since the upstream pre-tokenizer uses them, they are also
457+
// included here (see https://huggingface.co/facebook/chameleon-7b).
458+
regex_exprs = {
459+
"<sentinel:[0-9]+>", // Sentinel tokens
460+
"(IMGIMG)((A|B|C|D|E|F|G|H|I){1,4})Z", // Image tokens
461+
"([\\t\\n]| | )", // directly from tokenizer.json
462+
"\\p{N}", // Individual digits
463+
"[\\p{P}!-/:-@\\[-`{-~]", // Punctuation, Isolated
464+
"'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
465+
};
466+
break;
453467
default:
454468
// default regex for BPE tokenization pre-processing
455469
regex_exprs = {

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